[Federal Register Volume 64, Number 70 (Tuesday, April 13, 1999)]
[Proposed Rules]
[Pages 18084-18300]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 99-8808]



[[Page 18083]]

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Part II





Department of Housing and Urban Development





_______________________________________________________________________
Office of Federal Housing Enterprise Oversight
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12 CFR Part 1750



Risk-Based Capital; Proposed Rule

  Federal Register / Vol. 64, No. 70 / Tuesday, April 13, 1999 / 
Proposed Rules  

[[Page 18084]]



DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT

Office of Federal Housing Enterprise Oversight

12 CFR Part 1750

RIN 2550-AA02


Risk-Based Capital

AGENCY: Office of Federal Housing Enterprise Oversight, HUD.

ACTION: Notice of proposed rulemaking.

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SUMMARY: The Office of Federal Housing Enterprise Oversight (OFHEO) is 
directed by the Federal Housing Enterprises Financial Safety and 
Soundness Act of 1992 to develop a risk-based capital regulation for 
Freddie Mac and Fannie Mae (collectively, the Enterprises). The 
regulation specifies the risk-based capital stress test that will 
determine the amount of capital an Enterprise is required to hold to 
maintain positive capital throughout a ten-year period of economic 
stress. The results of the risk-based capital stress test will be used 
to determine each Enterprise's risk-based capital requirements and, 
along with the minimum capital requirement, to determine each 
Enterprise's capital classification for purposes of possible 
supervisory action.
    This Notice of Proposed Rulemaking is the second of two notices of 
proposed rulemaking pertaining to the risk-based capital regulation, 
both of which respond to comments received on the Advance Notice of 
Proposed Rulemaking. The first Notice of Proposed Rulemaking describes 
the methodology and rationale OFHEO used to identify the proposed 
benchmark loss experience, which is used to determine Enterprise credit 
losses during the stress test, and proposes the use of OFHEO's House 
Price Index in the stress test. The second Notice of Proposed 
Rulemaking specifies the interest rate risk and other components of the 
stress test, as well as the overall structure of the test.

DATES: Comments regarding this NPR must be received in writing on or 
before August 11, 1999.

ADDRESSES: Send written comments to Anne E. Dewey, General Counsel, 
Office of General Counsel, Office of Federal Housing Enterprise 
Oversight, 1700 G Street, NW., Fourth Floor, Washington, D.C. 20552. 
Written comments may also be sent by electronic mail at 
[email protected].

FOR FURTHER INFORMATION CONTACT: Patrick J. Lawler, Director of Policy 
Analysis and Chief Economist; David J. Pearl, Director, Office of 
Research, Analysis and Capital Standards; or Gary L. Norton, Deputy 
General Counsel, Office of General Counsel, Office of Federal Housing 
Enterprise Oversight, 1700 G Street, NW., Fourth Floor, Washington, 
D.C. 20552, telephone (202) 414-3800 (not a toll-free number). The 
telephone number for the Telecommunications Device for the Deaf is 
(800) 877-8339.

SUPPLEMENTARY INFORMATION: The Supplementary Information is organized 
according to this table of contents:

I. Introduction
    A. Background
    B. Statutory Requirements for Risk-Based Capital
    C. History of the Development of the Regulation
II. Structure and Operation of the Regulation
    A. Summary of the Stress Test
    1. Introduction
    2. Data
    3. Stress Test Conditions
    4. Mortgage Performance
    5. Other Credit Factors
    6. Cash Flows
    7. Enterprise Operations & Taxes
    8. Financial Reporting
    9. Calculation of the Risk-based Capital Requirement
    B. Sensitivity of Capital Requirement to Risk
    1. MBS Guarantees (Sold Loans)
    2. Commitments
    3. Assets and Liabilities
    4. Administrative Costs
    5. External Economic Conditions
    C. Implications of the Proposed Rule
    1. Capital Requirements Under the Proposed Rule
    2. Enterprise Adjustments to Meet the Proposed Standard
    3. Guarantee Fees
    4. Mortgage Interest Rates
III. Issues, Alternatives Considered
    A. Mortgage Performance
    1. Statutory Requirements
    2. Overview of Mortgage Performance
    3. Statistical Models of Mortgage Performance
    4. General Methodological Issues
    5. Default/Prepayment Issues
    6. Loss Severity
    7. Relating Losses to the Benchmark Loss Experience
    8. Inflation Adjustment
    B. Interest Rates
    1. Yields on Treasury Securities
    2. Yields of Non-Treasury Instruments
    C. Mortgage Credit Enhancements
    1. Background
    2. Modeling Approach
    3. Comments and Alternatives Considered
    D. Liabilities and Derivatives
    1. Modeling Methodology
    2. Foreign Currency Linked or Unusual Instruments
    3. Call and Cancellation Options
    4. Counterparty Risk
    E. Non-mortgage Investments
    F. Other Housing Assets
    1. Mortgage Revenue Bonds
    2. Private Label REMICs
    3. Interests in Partnerships and Joint Ventures
    G. Commitments
    1. Definition of the Term ``Commitment''
    2. Retained vs. Securitized Mortgages
    3. Modeling Delivery Percentages
    4. Delivery Timing
    5. Loan Mix Distribution
    6. No New Business Rule
    H. New Debt and Investment Rules
    1. Rationale for New Debt and New Investment Rules
    2. Analysis of ANPR Comments
    I. Operating Expenses
    J. Dividends and Other Capital Distributions
    1. Introduction
    2. Statutory Provisions
    3. Proposed Approach
    4. Analysis of ANPR Comments
    K. Other Off-Balance Sheet Guarantees
    L. Calculation of the Risk-Based Capital Requirement
    1. Proposed Approach to Calculating Capital
    2. Justification for Using a Present Value Approach
IV. Technical Supplement
    A. Purpose and Scope
    B. Single Family Default/Prepayment
    1. Introduction
    2. Conceptual Framework
    3. Data
    4. Specification of the Statistical Model
    5. Explanatory Variables for Default and Prepayment
    6. Empirical Results
    7. Application of the Models in the Stress Test
    8. Consistency with the Historical Benchmark Experience
    9. References
    C. Single Family Loss Severity
    1. Introduction
    2. Conceptual Framework
    3. Data
    4. Statistical Analysis
    5. Consistency with the Benchmark Loss Experience
    6. Application to the Stress Test
    7. References
    D. Multifamily Default/Prepayment
    1. Introduction and Conceptual Framework
    2. Historical Data
    3. Statistical Estimation
    4. Explanatory Variables
    5. Results of the Statistical Estimation of Default and 
Prepayment Equations
    6. Application to the Stress Test
    7. References
    E. Multifamily Loss Severity
    1. Introduction
    2. Conceptual Framework
    3. Sources of Data
    4. Data Analysis
    5. Application to the Stress Test
    6. References
    F. Property Valuation
    1. Introduction
    2. Conceptual Framework
    3. Data Sources
    4. Statistical Analysis
V. Regulatory Impact
    A. Executive Order 12612, Federalism
    B. Executive Order 12866, Regulatory Planning and Review

[[Page 18085]]

    C. Executive Order 12988, Civil Justice Reform
    D. Regulatory Flexibility Act
    E. Paperwork Reduction Act

I. Introduction

A. Background

    The Office of Federal Housing Enterprise Oversight (OFHEO) was 
established by title XIII of the Housing and Community Development Act 
of 1992, Pub. L. No. 102-550, known as the Federal Housing Enterprises 
Financial Safety and Soundness Act of 1992 (1992 Act). OFHEO is an 
independent office within the U.S. Department of Housing and Urban 
Development (HUD) with responsibility for ensuring that the Federal 
Home Loan Mortgage Corporation (Freddie Mac) and the Federal National 
Mortgage Association (Fannie Mae) (collectively, the Enterprises) are 
adequately capitalized and operating in a safe and sound manner. 
Included among the express statutory authorities of OFHEO's Director 
(the Director) is the authority to issue regulations establishing 
minimum and risk-based capital standards.\1\
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    \1\ 1992 Act, section 1313(b)(1) (12 U.S.C. 4513(b)(1)).
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    Fannie Mae and Freddie Mac are Government-sponsored Enterprises 
with important public purposes.\2\ These include providing liquidity to 
the residential mortgage market and increasing the availability of 
mortgage credit benefiting low-and moderate-income families and areas 
that are underserved by lending institutions. The Enterprises engage in 
two principal businesses: investing in residential mortgages and 
guaranteeing securities backed by residential mortgages. The securities 
the Enterprises guarantee and the debt instruments they issue are not 
backed by the full faith and credit of the United States and nothing in 
this document should be construed otherwise.\3\ Yet financial markets 
accord the Enterprises' securities preferential treatment relative to 
securities issued by potentially higher-capitalized, fully private, but 
otherwise comparable firms. The market prices for Enterprise debt and 
mortgage-backed securities, and the fact that the market does not 
require that those securities be rated by a national rating agency, 
suggest that investors perceive that the government implicitly 
guarantees those securities. This perception evidently arises from the 
public purposes of the Enterprises, their Congressional charters, their 
potential direct access to U.S. Department of Treasury (Treasury) 
funds, and the statutory exemptions of their debt and mortgage-backed 
securities (MBS) from otherwise mandatory investor protection 
provisions.\4\
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    \2\ 1992 Act, sections 1331-38 (12 U.S.C. 4561-67, 4562 note).
    \3\ See, Federal Home Loan Mortgage Corporation Act, section 
306(h)(2) (12 U.S.C. 1455(h)(2)); Federal National Mortgage 
Association Charter Act, section 304(b) (12 U.S.C. 1719(b)); and 
1992 Act, section 1302(4) (12 U.S.C. 4501(4)).
    \4\ See, e.g., 12 U.S.C. 24 (authorizing unlimited investment by 
national banks in obligations of or issued by the Enterprises); 12 
U.S.C. 1455(g), 1719(d), 1723(c) (exempting securities from 
oversight from Federal regulators); 15 U.S.C. 77r-1(a) (preempting 
State law that would treat Enterprise securities differently from 
obligations of the United States for investment purposes); 15 U.S.C. 
77r-1(c) (exempting Enterprise securities from State blue sky laws).
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    Congress created OFHEO as the safety and soundness regulator of the 
Enterprises to reduce their risk of failure. Although each Enterprise 
at the time had experienced profitability and sustained growth, 
Congress determined that there was a need for a strong and independent 
regulator to promote the capital adequacy of the Enterprises. This 
determination was grounded in the recognition of many factors, 
including (1) the important public purpose served by the Enterprises in 
the secondary market for residential mortgages, and (2) the 
Enterprises' important role in providing access to mortgage credit in 
central cities, rural regions, and underserved areas.
    Another important factor leading to OFHEO's creation was the 
recognition that the Enterprises are largely insulated from private 
market discipline relative to fully private firms. This insulation 
results from the apparent investor perception of an implied guarantee, 
and is best exemplified by the market's acceptance of Fannie Mae 
securities in the early 1980s and the Farm Credit System's securities 
in the mid-1980s when these GSEs were experiencing financial 
difficulties. The absence of normal market discipline on risk-taking is 
a strong argument for effective government regulation, including 
capital regulation.
    Congress was also concerned about the serious disruptions to the 
nation's housing markets that could result from an Enterprise's 
failure. In introducing legislation in the House of Representatives, 
then House Banking Committee Chairman Henry Gonzalez noted that--

    The savings and loan crisis and the large losses incurred by the 
Federal Government to resolve the crisis, raises concerns about the 
scope of other potential liabilities of the United States, including 
the liabilities of Fannie Mae, Freddie Mac, and the [Federal Home 
Loan] banks. These entities are privately owned federally chartered 
enterprises established to meet certain credit needs. Together they 
have more than $800 billion in mortgage-related liabilities.\5\
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    \5\ Comments by Rep. Gonzalez upon introducing H.R. 2900, 137 
Cong. Rec. H5497 (July 16, 1991).

    In expressing his view that the legislation did not go far enough 
to ensure the Enterprises' safety and soundness, then Ranking Minority 
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Member Jim Leach stated that--

    If there is a singular lesson of the 1980's, it is that 
prudential capital ratios are critical not only for providing a 
cushion between an institution's liabilities and the taxpayer's 
pocket book, but they ground institutional decision-making in less 
risky behavior. Where there is minimal private capital at risk there 
is always an inordinate incentive to bet the bank on speculative 
investments or interest rate moves. And perhaps most consequently, 
capital ratios determine constraints on growth. If institutions are 
allowed 50 or 100 to 1 leveraging, as occurred so recently in the 
thrift industry, imprudent or conflict driven decision making can 
too quickly cause disproportionate growth in certain institutions, 
industries and parts of the country, with the taxpayer on the line 
for management stupidity, foul play or bad luck.
    Fortunately, both GSEs are well run today. Fannie, in particular 
has been a major market winner as the cost of funds has declined 
with more restrained levels of inflation. But Congress must 
understand that if interest rates had gone up rather than down in 
the 1980's, Fannie Mae would be the single largest institutional 
liability the U.S. government would ever have been forced to 
oversee.\6\
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    \6\ Dissenting views of Rep. Leach, Government-Sponsored Housing 
Enterprises Financial Safety and Soundness Act of 1991, H.R. Rep. 
No. 102-206 on H.R. 2900, at 114 (1991) (House Report).

    Similarly, the Senate Report \7\ stated that--
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    \7\ Federal Housing Enterprises Regulatory Reform Act of 1992, 
S. Rep. No. 102-282 (1992) (Senate Report).

    Past performance indicates that [the risks of an Enterprise's 
failure] are not just hypothetical. While both GSEs are currently 
very prosperous, HUD estimated in a 1986 report to Congress, that 
Fannie Mae was insolvent on a marked-to-market basis at year-end 
1978 and did not return to solvency until 1985. Its negative net 
worth reached a peak of more than $20 billion in 1981, which was 
roughly 20 percent of its outstanding liabilities. Its recovery owed 
partly to improved management, but also, in considerable measure to 
fortuitous declines in interest rates.\8\
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    \8\ S. Rep. No. 102-282, at 10 (1992).

    Because of Congress' concerns, OFHEO was established as the safety 
and soundness regulator of Fannie Mae and Freddie Mac. OFHEO is 
responsible for conducting examinations to ensure the Enterprises' 
safety and soundness and establishing and enforcing compliance with two 
types of capital

[[Page 18086]]

standards required by the 1992 Act. The first is the minimum capital 
standard.\9\ Using this standard, which is based on a set of leverage 
ratios, OFHEO has classified each Enterprise's capital position every 
quarter since OFHEO's inception. After initially using an interim 
procedure, OFHEO published a rule regarding minimum capital, which 
incorporates a more careful evaluation of the credit risks associated 
with swaps and other off-balance sheet obligations.\10\ The resulting 
standard is comparable in its construction to the risk-based capital 
standards of other financial institution regulators.
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    \9\ 1992 Act, section 1362 (12 U.S.C. 4612).
    \10\ 12 CFR 1750.4; see Minimum Capital, Final Rule, 61 FR 
35607, July 8, 1996.
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    The second capital standard required by the 1992 Act is the risk-
based capital standard. This standard requires each Enterprise to hold 
sufficient capital to survive a ten-year period characterized by 
adverse credit losses and large movements in interest rates, plus an 
additional amount to cover management and operations risk.\11\ The 
level of capital \12\ required under this standard for an Enterprise 
will reflect that Enterprise's specific risk profile at the beginning 
of each quarter for which the stress test will be run.
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    \11\ 1992 Act, section 1361 (12 U.S.C. 4611).
    \12\ For purposes of the risk-based capital standard, the term 
``capital'' means ``total capital'' as defined under section 
1303(18) of the 1992 Act (12 U.S.C. 4502(18)) to mean the sum of the 
following:
    (A) The core capital of the enterprise;
    (B) A general allowance for foreclosure losses, which--
    (i) shall include an allowance for portfolio mortgage losses, an 
allowance for nonreimbursable foreclosure costs on government 
claims, and an allowance for liabilities reflected on the balance 
sheet for the enterprise for estimated foreclosure losses on 
mortgage-backed securities; and
    (ii) shall not include any reserves of the enterprise made or 
held against specific assets.
    (C) Any other amounts from sources of funds available to absorb 
losses incurred by the enterprise, that the Director by regulation 
determines are appropriate to include in determining total capital.
    The term ``core capital'' is defined under section 1303(4) of 
the 1992 Act (12 U.S.C. 4502(4)) to mean the sum of the following 
(as determined in accordance with generally accepted accounting 
principles):
    (A) The par or stated value of outstanding common stock.
    (B) The par or stated value of outstanding perpetual, 
noncumulative preferred stock.
    (C) Paid-in capital.
    (D) Retained earnings.
    The core capital of an enterprise shall not include any amounts 
that the enterprise could be required to pay, at the option of 
investors, to retire capital instruments.
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    The risk-based standard is an essential component of the safety and 
soundness regulation of the Enterprises. Without the risk-based 
standard, an Enterprise might adopt risk positions of sufficient 
magnitude to make a capital level that just meets the minimum standard 
inadequate for maintaining a safe and sound financial condition.
    However, the risk-based standard cannot, by itself, ensure 
sufficient capital to meet all contingencies. While the interest rate 
and credit stresses that are incorporated in the stress test, as 
specified by statute, are historically unprecedented, future economic 
environments may be even more adverse. Additionally, the nature of 
actual future stresses may differ from the precise stresses 
incorporated in the model. Furthermore, the model contains factors such 
as mortgage default and prepayment rates that are based on historical 
experience and therefore may be less adverse than those actually 
occurring in future economic environments. Similarly, the consequences 
of risks other than interest rate and credit risks may also prove more 
serious than the fixed proportional amount allowed for management and 
operations risk.
    In addition to the risk-based standard, there is a minimum capital 
standard, which requires that in the absence of large measurable risks, 
the Enterprise maintain a minimally acceptable level of capital. 
Complementing the two capital standards are OFHEO's examination and 
enforcement authorities, which provide the knowledge and authority 
necessary to require prudent management practices in all environments. 
All of these regulatory mechanisms operate in tandem to promote the 
safety and soundness of the Enterprises.

B. Statutory Requirements for Risk-Based Capital

    The 1992 Act requires that OFHEO, by regulation, establish a risk-
based capital test (known as the stress test) which, when applied to an 
Enterprise, shall determine that amount of total capital for the 
Enterprise that is sufficient for the Enterprise to maintain positive 
capital during the stress period. The 1992 Act also provides that, in 
order to meet its risk-based capital standard, each Enterprise is 
required to maintain an additional 30 percent of this amount to protect 
against management and operations risk.\13\
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    \13\ 1992 Act, section 1361(c)(2) (12 U.S.C. 4611(c)(2)).
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    The 1992 Act requires that the stress test subject each Enterprise 
to large credit losses on mortgages it owns or guarantees. The 
frequency and severity of those losses must be reasonably related to 
the highest rates of default and severity of mortgage losses 
experienced during a period of at least two consecutive years in 
contiguous areas of the United States that together contain at least 
five percent of the total U.S. population.\14\ OFHEO is required to 
identify what it has characterized as the ``benchmark loss experience'' 
that resulted in the highest loss rate.\15\ In this context, default 
and severity behavior means the frequency, timing, and severity of 
losses on mortgage loans, given the specific characteristics of those 
loans and the economic circumstances affecting those losses.
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    \14\ 1992 Act, section 1361(a)(1) (12 U.S.C. 4611(a)(1)).
    \15\ In this document, the word ``benchmark,'' when used as an 
adjective or a noun, refers to the benchmark loss experience.
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    The 1992 Act also prescribes two interest rate scenarios, one with 
rates falling and the other with rates rising.\16\ The risk-based 
capital amount is based on whichever scenario would require more 
capital for the Enterprise. In prescribing the two scenarios, the 1992 
Act describes the path of the ten-year constant maturity yield (CMT) 
for each scenario and directs OFHEO to establish the yields on Treasury 
instruments of other maturities in a manner reasonably related to 
historical experience and judged reasonable by the Director.
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    \16\ 1992 Act, section 1361(a)(2) (12 U.S.C. 4611(a)(2)).
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    In the falling or down-rate scenario, the ten-year CMT decreases 
during the first year of the stress period and then remains constant at 
the lesser of (a) 600 basis points below the average yield during the 
nine months preceding the stress period or (b) 60 percent of the 
average yield during the three years preceding the stress period. 
However, the 1992 Act limits the decrease in yield to 50 percent of the 
average yield in the nine months preceding the stress period.\17\
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    \17\ 1992 Act, section 1361(a)(2)(B) (12 U.S.C. 4611(a)(2)(B)).
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    In the rising or up-rate scenario, the ten-year CMT increases 
during the first year of the stress period and then remains constant at 
the greater of (a) 600 basis points above the average yield during the 
nine months preceding the stress period or (b) 160 percent of the 
average yield during the three years preceding the stress period. 
However, the 1992 Act limits the increase in yield to 175 percent of 
the average yield over the nine months preceding the stress period.\18\ 
The 1992 Act recognizes that interest rates can affect credit risk, 
specifically requiring that credit losses be adjusted for a 
correspondingly higher rate of general price inflation if

[[Page 18087]]

application of the stress test produces an increase of more than 50 
percent in the ten-year CMT.\19\
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    \18\ 1992 Act, section 1361(a)(2)(C) (12 U.S.C. 4611(a)(2)(C)).
    \19\ 1992 Act, section 1361(a)(2)(E) (12 U.S.C. 4611(a)(2)(E)).
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    The Act requires that the stress test take into account 
distinctions among mortgage product types and differences in seasoning. 
It may also take into account any other factors that the Director deems 
appropriate. The 1992 Act does not require a specific adjustment for 
any of these factors, allowing the Director to determine how best to 
account for them. Likewise, the 1992 Act requires the Director to 
determine losses and gains on Enterprise activities not specifically 
addressed, and all other characteristics of the stress test not 
explicitly defined in the 1992 Act, on the basis of available 
information, in a manner consistent with the stress test.\20\ These 
stress test characteristics could include, among others, mortgage 
prepayment rates and Enterprise funding activities, operating expenses, 
and capital distribution activities.
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    \20\ 1992 Act, sections 1361(b) and (d)(2) (12 U.S.C. 4611(b) 
and (d)(2)).
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    The 1992 Act requires the stress test to provide initially that 
each Enterprise will conduct no new business within the stress period, 
except to fulfill contractual commitments to purchase mortgages or 
issue securities. Four years after the final risk-based capital 
regulation is issued, OFHEO is authorized to modify the stress test to 
incorporate assumptions about additional new business conducted during 
the stress period.\21\ In doing so, OFHEO is required to take into 
consideration the results of studies conducted by the Congressional 
Budget Office and the Comptroller General of the United States on the 
advisability and appropriate forms of new business assumptions. The 
1992 Act requires that the studies be completed within the first year 
after issuance of the final regulation.\22\
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    \21\ 1992 Act, sections 1361(a)(3)(B) and (D) (12 U.S.C. 
4611(a)(3)(B) and (D)).
    \22\ 1992 Act, section 1361(a)(3)(C) (12 U.S.C. 4611(a)(3)(C)).
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    In developing this proposal, OFHEO considered whether it would be 
permissible and appropriate not to propose a detailed risk model, and 
instead to rely on the risk models developed by the Enterprises 
themselves.\23\ Under such a regulatory approach, OFHEO would specify 
only the basic interest rate and credit assumptions, rely on the 
Enterprises' internal modeling of these scenarios and review those 
models and the results.
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    \23\ This approach, which OFHEO considered in detail as it began 
to develop the risk-based capital regulation, was raised most 
recently by Fannie Mae during the OMB review process. See the 
letters from Ms. Jamie S. Gorelick, Vice Chair, Fannie Mae of 
December 4, 1998 to various OMB officials; and of March 10, 1999, to 
Dr. Janet Yellen, Chair, Council of Economic Advisers.
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    OFHEO has thoroughly considered this approach and believes that it 
would not be consistent with the 1992 Act, which anticipates that a 
publicly-available, transparent and reproducible test would be applied 
to the Enterprises. The 1992 Act provides for both Enterprises to be 
subject to the same stress test; \24\ that the full test be subject to 
notice and comment rulemaking; \25\ that the risk-based capital 
regulation be sufficiently specific to permit anyone to apply the test, 
given relevant Enterprise data; \26\ and that OFHEO must make the 
stress test model public.\27\ Relying on the Enterprises to compute 
their own capital requirements with their proprietary models would be 
inconsistent with all of these provisions.
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    \24\ See 12 U.S.C. 4611(a) (``The Director shall, by regulation, 
establish a risk-based capital test for the Enterprises. When 
applied to an Enterprise, the risk-based capital test shall 
determine the amount of total capital for the Enterprise . . .'') 
(emphasis added). See also H.R. Rep. No. 102-206 at 62 (1991). 
(``Beyond these traditional capital ratios, the bill sets forth 
guidelines for the creation, in highly specific regulations, of a 
risk-based capital standard . . . The model, or stress test, will 
generate a number for each Enterprise, which will become the risk-
based standard for that Enterprise.'') (emphasis added).
    \25\ Section 1361(e)(1), 12 U.S.C. 4611(e)(1).
    \26\ Section 1361(e)(2), 12 U.S.C. 4611(e)(2).
    \27\ Section 1361(f), 12 U.S.C. 4611(f).
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    Moreover, a rule that specifies the details of the model will 
provide a more consistent and effective capital regulation and will not 
place undue burdens on the Enterprises. The structure of OFHEO's 
regulatory and enforcement authorities presumes a strong risk-based 
capital standard. The level of the minimum (leverage) capital standard 
was established with the assumption that there would be a meaningful 
risk-based standard that would address actual or potential risk not 
addressed by simple leverage ratios. In addition, important OFHEO 
enforcement authorities are tied to the risk-based capital requirement. 
An Enterprise's failure to meet these requirements triggers two 
important enforcement authorities: the ability to reduce or eliminate 
the Enterprise's dividends and the ability to require a capital 
restoration plan acceptable to OFHEO. Also, the grounds for a cease and 
desist action vary depending on whether an Enterprise meets the risk-
based standard. Thus, a weaker standard would weaken OFHEO's 
enforcement authorities.
    These objectives are best obtained by a clear standard that is 
presented to the public for comment and then employed consistently to 
evaluate both Enterprises. Reliance instead on Enterprise models would 
likely result in a weaker inconsistently-applied standard. Use of 
Enterprise models would give the Enterprises broad discretion to 
determine their own risk-based capital requirements because stress test 
details beyond basic assumptions and modeling techniques can have a 
substantial cumulative effect on the results. Existing market 
distortions would give the Enterprises incentives to adjust those 
details to produce low requirements.
    The Enterprises' status as government-sponsored-enterprises 
attenuates market discipline of Enterprise capital levels. The 
Enterprises are highly leveraged financial institutions. Fully private 
firms that depend heavily on debt markets are inhibited from taking on 
large amounts of risk relative to their equity capital. Interest rates 
on debt or guaranteed securities are sensitive to the perceived credit 
quality of the issuers or guarantors. However, because investors treat 
Enterprise obligations as implicitly guaranteed by the Federal 
government, the normal linkage between the adequacy of an Enterprise's 
capital and the interest rates on its obligations is severed. Thus, 
because of the perceived implicit guarantee, the Enterprises have an 
incentive to hold less capital, relative to their risk levels, than 
they would if their debt costs were subject to normal market forces. A 
strong risk-based capital standard can address this distortion, but the 
Enterprises have little incentive to assist in producing such a result.
    Reliance on different Enterprise internal models would also result 
in unequal treatment. The nature of business risks and risk management 
techniques are very similar at the two Enterprises. It is most 
appropriate and most fair to determine each Enterprise's capital 
adequacy in the same way. However, capital models developed by the two 
Enterprises would likely differ significantly. Differences in resulting 
standards could easily mask significant differences in true capital 
adequacy between the Enterprises. Furthermore, a lower effective 
standard at one Enterprise could give that Enterprise important 
business advantages over the other. The resulting competitive pressures 
would give the Enterprise with the higher standard an incentive to 
conform with the lower standard.
    A model fully specified in regulation and administered by OFHEO, on 
the other hand, does not suffer these disadvantages. Such a model is 
feasible

[[Page 18088]]

because OFHEO regulates only two institutions, with similar risks and 
relatively narrow lines of business. The transparency of this approach 
allows all interested parties to comment meaningfully on the precise 
method of determining Enterprise capital requirements, and it gives the 
Enterprises the ability to internalize the model for planning purposes.
    In analyzing this issue, OFHEO is aware that some Federal financial 
institution regulators make limited use of internal models. However, 
those uses of internal models are made in very different circumstances 
and by regulators with different authorizing statutes. Many of the 
institutions in which these regulators rely upon internal models are 
exposed to substantial market discipline of their capital and risk 
positions because they rely heavily on uninsured liabilities. Such 
discipline effectively forces large banks to hold capital well in 
excess of regulatory requirements.
    Even in these circumstances, other regulators depend on internal 
models only to a small extent as a supplement to other measures of 
capital adequacy. Bank capital requirements are primarily based on 
overall or risk-weighted ratios that are substantially higher than 
those applied to the Enterprises under the minimum capital standard. To 
supplement those ratios, regulators require banks with significant 
market risk exposures (those that have large trading accounts) to use 
their internal value-at-risk models to calculate a market-risk capital 
component of their overall risk-based capital requirements. However, 
partly because of the uncertainties surrounding model construction and 
verification, bank regulators require a multiple of three or more times 
the amount of capital for market risk exposures that the internal 
models estimate.\28\ This limited use of internal models in very 
different circumstances does not appear applicable to Enterprise 
capital regulation.
---------------------------------------------------------------------------

    \28\ See, for example, Darryll Hendricks and Beverly Hirtle, 
``Bank Capital Requirements for Market Risk: The Internal Models 
Approach,'' in Economic Policy Review, Federal Reserve Bank of New 
York, December 1997, pp. 3-6.
---------------------------------------------------------------------------

    OFHEO considered whether an internal models approach could permit 
greater flexibility and innovation by the Enterprises, because they 
could modify their internal risk models at will. OFHEO believes the 
issues of flexibility and innovation have been appropriately addressed 
in the proposed regulation. In general, OFHEO expects that credit and 
interest rate risk of new Enterprise activities and instruments will be 
reflected in the stress test by simulating their credit and cash flow 
characteristics using the approaches described in the regulation. OFHEO 
will provide the Enterprises with its estimate of the capital treatment 
of new products, investments or instruments as soon as possible after 
the Enterprises notify OFHEO of the new activities. In addition, OFHEO 
will monitor the Enterprises' activities and, when appropriate, propose 
amendments to this regulation addressing the treatment of new 
instruments and activities.
    For all the reasons described, OFHEO believes that the approach 
proposed in this Notice implements the requirement of the 1992 Act and 
provides an appropriate means for ensuring the capital adequacy of the 
Enterprises. In accordance with the requirements of the Administrative 
Procedure Act, OFHEO is requesting comments on all of the issues raised 
in this Notice of Proposed Rulemaking.

C. History of the Development of the Regulation

    OFHEO's mission is to ensure that the Enterprises are adequately 
capitalized and operating in a safe and sound manner. The principal 
objective of the risk-based capital standard is to reduce the risk of 
Enterprise insolvency. Another important objective of the risk-based 
capital standard is to align the incentives reflected in the regulatory 
capital requirement with the incentives of prudent risk management. The 
ultimate goal is for the Enterprises to maintain the financial health 
necessary to fulfill their public purposes. Although the stress test 
produces a single capital requirement, it effectively creates 
incremental regulatory capital requirements for each additional dollar 
of business for every product type an Enterprise guarantees or holds in 
portfolio. Marginal capital requirements for mortgages held in 
portfolio will vary depending on the risk inherent in an Enterprise's 
funding strategy.
    OFHEO designed the stress test so that the incentives it creates 
closely reflect the relative risks inherent in the Enterprises' 
different activities. To this end, the proposed regulation 
incorporates, to the extent feasible, consistent relationships between 
the economic environment of the stress period and the Enterprises' 
businesses. Doing so required OFHEO to model the Enterprises' assets, 
liabilities, and off-balance sheet positions at a sufficient level of 
detail to capture important risk characteristics.
    However, as the level of detail of the stress test increased, so 
did its complexity, along with the time and other resources that were 
required to develop it. OFHEO also faced certain practical limits to 
the number of variables that could be modeled due to the limitations of 
existing data. Therefore, in developing this proposed regulation, OFHEO 
sought to achieve a level of complexity and realism in the stress test 
that appropriately balanced the associated benefits and costs.
    OFHEO's stress test is comprised of a number of components, some 
that correspond to subjects specifically cited in the 1992 Act and 
others that represent the infrastructure that makes the stress test 
operational. Figure 1 illustrates these components and their 
interrelationships. The infrastructure components--database, cash 
flows, and financial reports--are shaded gray. The unshaded components 
implement the specific requirements of the 1992 Act, as well as the 
many other aspects of the stress test that the 1992 Act either requires 
or permits OFHEO to determine.

[[Page 18089]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.369


    On February 8, 1995, OFHEO published an Advance Notice of Proposed 
Rulemaking (ANPR) \29\ as its first step in developing the risk-based 
capital regulation. The ANPR announced OFHEO's intention to develop and 
publish a risk-based capital regulation and solicited public comment on 
issues relating to that regulation.
---------------------------------------------------------------------------

    \29\ Risk-Based Capital, ANPR, 60 FR 7468, February 8, 1995.
---------------------------------------------------------------------------

    The comment period for the ANPR ended on May 9, 1995, and was 
extended through June 8, 1995.\30\ OFHEO received 17 comments on the 
ANPR from a variety of interested parties. Commenters included two 
Executive Branch Departments, HUD and Department of Veterans Affairs 
(VA); one Federal financial institution regulatory agency Office of 
Thrift Supervision (OTS); one Federal regulatory agency, U.S. Commodity 
Futures Trading Commission (CFTC); the Enterprises, Fannie Mae and 
Freddie Mac; four trade groups, Mortgage Bankers Association of America 
(MBA), America's Community Bankers (ACB), National Association of 
Realtors (NAR), and Mortgage Insurance Companies of America (MICA); two 
mortgage banking firms, PNC Mortgage Corporation of America and Norwest 
Mortgage, Inc.), one rating agency Standard and Poor's Ratings Group 
(S&P); one thrift institution, World Savings and Loan Association 
(MS&L); one private mortgage research firm, Mortgage Risk Assessment 
Corporation (MRAC); and one individual, Professor Anthony Yezer of 
George Washington University. The responses to the ANPR ranged from a 
comment on only one or two specific risk-based capital issues to an 
extensive analysis of every question or issue raised. OFHEO has 
considered these comments in the development of its risk-based capital 
regulation.
---------------------------------------------------------------------------

    \30\ Risk-Based Capital, Extension of Public Comment Period for 
ANPR, 60 FR 25174, May 11, 1995.
---------------------------------------------------------------------------

    OFHEO determined that the scope of the regulatory project required 
the issuance of two separate Notices of Proposed Rulemaking (NPR), each 
addressing different components of the stress test. On June 11, 1996, 
OFHEO published a Notice of Proposed Rulemaking (NPR1),\31\ which 
addresses two components. The first component is the methodology for 
identifying and measuring the benchmark loss experience, which provides 
the basis for determining credit losses that the Enterprises will 
experience during the stress period. The second is OFHEO's proposal to 
use the OFHEO House Price Index (HPI), which is a weighted repeat 
transactions house price index, rather than the Constant Quality Home 
Price Index (CQHPI) published by the Secretary of Commerce, to measure 
differences in seasoning of single family mortgages in the stress 
test.\32\ NPR1 included OFHEO's responses to all of the ANPR comments 
that related to those two areas. The comment period for NPR1 ended on 
September 9, 1996, and was extended through October 24, 1996.\33\ OFHEO 
received 11 written comments on NPR1 and will consider and respond to 
those in the final risk-based capital regulation.
---------------------------------------------------------------------------

    \31\ Risk-Based Capital, NPR1, 61 FR 29592, June 11, 1996.
    \32\ 61 FR 29616, June 11, 1996.
    \33\ Risk-Based Capital, Extension of Public Comment Period for 
NPR, 61 FR 42824, August 19, 1996.
---------------------------------------------------------------------------

    This Notice of Proposed Rulemaking (NPR2) specifies and proposes 
for public comment all of the remaining aspects of the risk-based 
capital stress test not covered in NPR1. The notice includes an 
overview of the stress test, the stress test's sensitivity to risk, the 
implications of the stress test for the Enterprises, and specific 
issues related to the stress test. Among the specific issues discussed 
are mortgage performance (i.e., default, prepayment, and loss 
severity), interest rates, new debt and new investments, commitments, 
dividends and other

[[Page 18090]]

capital distributions, operating expenses, credit enhancements, 
liabilities and derivatives, non-mortgage investments, and capital 
calculation. The notice also includes a technical supplement that 
explains the derivation of equations used in the stress test. Finally 
the notice contains the regulatory text which includes the regulatory 
appendix that provides the technical details of the regulation.
    OFHEO believes that it is important for this proposal to receive 
full public review and comment. Accordingly, OFHEO invites all 
interested parties to comment on the issues raised in this NPR. OFHEO 
will consider comments received, together with those received on NPR1, 
in the development of the final risk-based capital regulation.

II. Structure and Operation of the Regulation

A. Summary of the Stress Test

1. Introduction
    OFHEO's risk-based capital regulation is part of a larger 
regulatory framework for the Enterprises that includes a minimum 
capital requirement and a comprehensive examination program. The 
purpose of this regulatory framework is to reduce the risk of failure 
of the Enterprises by ensuring that the Enterprises are adequately 
capitalized and operating safely, in accordance with the 1992 Act.
    OFHEO's risk-based capital requirement differs from the minimum 
capital requirement by relating the required capital to the risk in an 
Enterprise's financial activities. In order to determine risk-based 
capital for the Enterprises, OFHEO has been charged with creating a 
stress test that simulates the effects of ten years of adverse economic 
conditions on the existing assets and obligations of the Enterprises. 
Both the minimum and the risk-based capital requirements work in 
conjunction with OFHEO's examination program to ensure that the 
Enterprises are adequately capitalized and operating safely.
    In creating the proposed stress test, OFHEO had to ensure that it 
met all the statutory requirements outlined in the 1992 Act and that it 
accurately and appropriately captured the risks related to the business 
of the Enterprises. To accomplish this, OFHEO modeled both sides of the 
Enterprises' balance sheets, as well as their off-balance sheet 
obligations, at the level of detail necessary to capture the risk 
involved. In selecting among alternative approaches, OFHEO sought to 
minimize the possibility of perverse incentives in the stress test. The 
regulation was designed to ensure that stresses were appropriate in 
order to promote safety and soundness and ensure the Enterprises' 
ability to fulfill their important public missions.
    The stress test determines, as of a point in time, how much capital 
an Enterprise requires to survive the economically stressful conditions 
outlined by the 1992 Act. At a minimum, the stress test would be run on 
a quarterly basis. The stress test takes as inputs data on an 
Enterprise's assets and obligations, operations, interest rates, and 
the housing market. These data are used in econometric, financial, and 
accounting models to simulate Enterprise financial performance over a 
ten year period called the ``stress period.'' The stress test then 
computes the amount of starting capital that would permit an Enterprise 
to maintain a positive capital position throughout the stress period. 
To determine the risk-based capital requirement, the 1992 Act requires 
that 30 percent of this amount is added to cover management and 
operations risk.
    This summary provides a high level description of the stress test. 
For a more detailed description, refer to the Regulation Appendix. For 
explanations of the reasons for the approaches taken, refer to section 
III., Issues, Alternatives Considered. For detailed information on 
econometric models and historical property valuation-related indexes 
used in the stress test, refer to section IV., Technical Supplement. 
Throughout the summary, it may be helpful to refer to the stress test 
diagram, in section I., Introduction.
2. Data
    The stress test utilizes data characterizing at a point in time an 
Enterprise's assets, liabilities, and off-balance sheet obligations, as 
well as data on economic conditions. The Enterprises submit data to 
OFHEO for mortgages, securities, and derivative contracts at the 
instrument level, that is, for individual mortgages, securities, and 
contracts. OFHEO obtains data on economic conditions from public 
sources. All these data are referred to as ``starting position data'' 
for the date for which the stress test is run.
    For modeling efficiency, the stress test aggregates loans into 
groups of loans with common risk and cash flow characteristics (``loan 
groups''). For instance, 30-year fixed-rate mortgages for single family 
homes in the same geographic region, originated in the same year, with 
similar interest rates and LTVs,\34\ and held in an Enterprise's 
portfolio, are grouped together in one loan group. In this way, over 24 
million loans are aggregated into the minimum number of loan groups 
that captures important risk characteristics. These loan groups, 
instead of individual loans, are then used as inputs by the mortgage 
performance and cash flow components of the stress test.
---------------------------------------------------------------------------

    \34\ LTV is the loan to value ratio, which is the loan balance 
divided by the value of the property securing the loan.
---------------------------------------------------------------------------

    In addition to starting position data for existing loans, the 
stress test creates loan group data for the new mortgages that will be 
added during the stress test. The 1992 Act requires that the stress 
test simulate the fulfillment of the Enterprises' contractual 
commitments, outstanding at the start of the stress period, to purchase 
and/or securitize mortgages. The new mortgages that the stress test 
adds consist of four single family loan product types: 30-year fixed-
rate, 15-year fixed-rate, adjustable-rate, and balloon. The percentage 
of each type added is based on the relative proportions of those types 
of loans securitized by an Enterprise that were originated during the 
six months preceding the start of the stress period. The mix of LTV, 
region, guarantee fee, and other characteristics of these new loans 
also reflects the characteristics of the loans originated during the 
preceding six months. All new mortgages are securitized. In the down-
rate scenario, 100 percent of these loans are added during the first 
three months of the stress period; in the up-rate scenario, 75 percent 
of these loans are added during the first six months. These loan groups 
are then treated like the loan groups created for loans on the 
Enterprise's books at the start of the stress period.
    Because of the smaller number and greater diversity of the 
Enterprises' non-mortgage financial instruments (investments and debt), 
the stress test projects these cash flows at the individual instrument 
level, rather than at a grouped level. Data used for these projections 
include the instrument characteristics that are used to model 
securities, both investment and debt, as well as derivative contracts.
3. Stress Test Conditions
a. Benchmark Loss Experience
    In NPR1, OFHEO proposed the methodology for identifying the 
benchmark loss experience, the stressful credit conditions which are 
the basis for credit losses in the stress test. With this methodology, 
OFHEO identified the worst cumulative credit losses

[[Page 18091]]

experienced by loans originated during a period of at least two 
consecutive years, in contiguous states encompassing at least five 
percent of the U.S. population. The performance of these loans (i.e., 
the frequency, timing and severity of their losses) and the related 
interest rate and housing market environment, comprise the benchmark 
loss experience.
    The benchmark loss experience is based on newly originated, 30-
year, fixed-rate, first lien mortgages on owner-occupied, single family 
properties. The performance of these benchmark loans was a function of 
their original LTVs and other characteristics, as well as the specific 
house price and interest rate paths they experienced. The stress test 
applies the path of house prices from the benchmark loss experience and 
the interest rate paths required by the 1992 Act. Furthermore, the 
stress test simulates the performance of an Enterprise's entire 
mortgage portfolio, including loans of all types, ages, and 
characteristics. Primarily for these reasons, overall Enterprise 
mortgage loss rates in the stress test are much lower than the loss 
rates OFHEO reported in NPR1 for benchmark loans.
    When the mortgage performance models are applied to benchmark 
loans, using the benchmark pattern of interest rates, losses are very 
close to those identified in NPR1. The remaining difference results 
from the fact that OFHEO based its mortgage performance models on all 
Enterprise historical loan data, not just the limited data for 
benchmark loans, and that the benchmark loss experience was 
particularly severe. This difference is corrected by calibrating the 
single family mortgage performance models, resulting in slight upward 
adjustments of default and loss severity rates, so that they are 
consistent with the benchmark loss experience.
    For multifamily loans, the stress test also incorporates patterns 
of vacancy rates and rent growth rates that are consistent with the 
benchmark loss experience. In this manner, the stress test relates the 
performance of multifamily loans to the benchmark loss experience.
b. Interest Rates
    Interest rates are a key component of the adverse economic 
conditions of the stress test. The 1992 Act specifies two scenarios for 
the ten-year Constant Maturity Treasury yield (CMT) during the stress 
period. During the first year of the stress period, the ten-year CMT:
     falls by the lesser of 600 basis points below the average 
yield during the nine months preceding the stress period, or 60 percent 
of the average yield during the three years preceding the stress 
period, but in no case to a yield less than 50 percent of the average 
yield during the preceding nine months (down-rate scenario); or
     rises by the greater of 600 basis points above the average 
yield during the nine months preceding the stress period, or 160 
percent of the average yield during the three years preceding the 
stress period, but in no case to a yield greater than 175 percent of 
the average yield during the preceding nine months (up-rate scenario).
    Changes to the ten-year CMT occur in twelve equal monthly 
increments from the starting point for the ten-year CMT, which is the 
average of the daily yields for the month preceding the stress period. 
The ten-year CMT stays at the new level for the remainder of the stress 
period.
    The stress test establishes the Treasury yield curve for the stress 
period in relation to the prescribed movements in the ten-year CMT. In 
the down-rate scenario the yield curve is upward sloping during the 
last nine years of the stress period. In the up-rate scenario the 
Treasury yield curve is flat for the last nine years of the stress 
period, that is, yields of other maturities are equal to that of the 
ten-year CMT.
    Because many different interest rates affect the Enterprises' 
business performance, the ten-year CMT and the Treasury yield curve are 
not the only interest rates that must be determined. For example, 
current mortgage rates affect rates of refinancing of existing 
mortgages; adjustable-rate mortgages periodically adjust according to 
various indexes; floating rate securities (assets and liabilities) and 
many rates associated with derivative contracts also adjust; and 
appropriate yields must be established for new debt and investments. 
Thus, the stress test requires rates and indexes other than Treasury 
yields for the entire period of the stress test. Some of the key rates 
that are estimated are the Federal Funds rate, London Inter-Bank 
Offered Rate (LIBOR), Federal Home Loan Bank 11th District Cost of 
Funds Index (COFI), and Enterprise borrowing rates. The stress test 
establishes these rates and indexes by using Autoregressive Integrated 
Moving Average (ARIMA) procedures--time-series estimation techniques--
to estimate their values based on historical spreads to yields on 
Treasuries of comparable maturities. The procedures use historical 
information to estimate values during the stress period. To reflect the 
market impact of stress test economic conditions on the Enterprises' 
costs of borrowing, beginning in the second year of the stress period, 
50 basis points are added to the computed yields for Enterprise debt 
securities.
c. Property Values
    In determining the performance (rates of default, prepayment, and 
of loss severity) of an Enterprise's mortgages in the stress test, the 
1992 Act requires OFHEO to consider seasoning, which the stress test 
captures by the use of current LTVs. The stress test calculates the 
numerator of current LTV, the current loan balance, based on the unpaid 
principal balance of the loan at the start of the stress period 
(starting UPB) and the amortization of the loan based on product type. 
Both the starting UPB and the loan product type are included in 
starting position data. The stress test uses the OFHEO HPI for the 
relevant Census division to track changes in property values--the 
denominator of current LTV--from the time of loan origination through 
to the start of the stress period. During the stress period, changes in 
property values are computed by applying the pattern of house price 
changes from the benchmark loss experience.
    The HPI values represent average property value appreciation. In 
simulating mortgage performance, the stress test also captures 
variations from average house price movements, called dispersion. For 
this purpose, the stress test uses the mathematical measures of 
dispersion that OFHEO publishes along with the HPI.
    For multifamily properties, property values are derived from 
estimates of a property's net operating income and capitalization rate 
multipliers. The stress test uses loan data together with rent growth 
rate and vacancy rate indexes to derive estimates of net operating 
income (NOI) for multifamily loans. Index values from the benchmark 
loss experience are applied to starting property values to derive 
current estimates of NOI for each month of the stress period. NOI is 
multiplied by a capitalization rate multiplier, reflecting current 
interest rates, to generate a property value. For example, if annual 
NOI is $200,000 and the capitalization rate multiplier is ten, the 
property value is $200,000 x 10, or $2,000,000. This value is the 
denominator for current LTV for multifamily loans.
    When the ten-year CMT increases by more than 50 percent over the 
average yield during the nine months preceding the stress period, the 
stress test takes general price inflation into consideration. 
Adjustments are made to the house price and rent growth paths of the 
benchmark loss experience equal to the percentage change in the ten-
year

[[Page 18092]]

CMT in excess of 50 percent.\35\ For example, if the ten-year CMT 
increases by 60 percent, house price and rent growth rates increase by 
ten percent. The stress test phases in this increase in equal monthly 
increments during the last five years of the stress period.
---------------------------------------------------------------------------

    \35\ The stress test computes the difference between the level 
of the ten-year CMT in the last nine years of the stress period and 
the level of the ten-year CMT if it had increased 50 percent. The 
difference in yield is compounded over a nine-year period to 
determine the cumulative percentage adjustment to house prices at 
the end of the stress period.
---------------------------------------------------------------------------

4. Mortgage Performance
    To simulate how mortgages fare during the adverse conditions of the 
stress period, the stress test uses models of mortgage performance, 
that project default, prepayment and loss severity rates. These models 
simulate the interaction of the patterns of house prices, residential 
rents, and vacancy rates of the benchmark loss experience, as well as 
stress test interest rates, and mortgage risk factors, in order to 
determine the performance of Enterprise loans for each month of the 
stress test. As described below in further detail, the models are based 
on the historical relationship of economic and mortgage risk factors to 
mortgage performance, as reflected in the historical experience of the 
Enterprises.
a. Loan Groups
    Rather than simulating the behavior of individual loans, the models 
simulate the behavior of groups of loans with common risk 
characteristics. The default and prepayment models calculate the 
proportion of the outstanding principal balance for each loan group 
that defaults, prepays, or makes regularly scheduled loan payments in 
each of the 120 months of the stress period. Single family loans are 
aggregated into loan groups based on key risk and cash flow 
characteristics: product type \36\ (e.g., 30-year fixed-rate, 15-year 
fixed-rate, adjustable rate, balloon), original LTV, interest rate, 
origination year, remittance cycle \37\ and Census division. 
Multifamily loans are similarly aggregated by product type, original 
LTV, origination year, interest rate, and Census region, as well as by 
debt coverage ratio (DCR) \38\ and program type. Program type 
distinguishes between loans purchased individually rather than as part 
of a pool, and loans subject to recourse or repurchase.\39\ These 
distinctions are associated with different risk characteristics.
---------------------------------------------------------------------------

    \36\ The 1992 Act requires that the stress test take into 
account appropriate distinctions among mortgage product types, 
including single or multifamily, fixed or adjustable interest rates 
and the term of the loans.
    \37\ For sold loans, the remittance cycle governs the length of 
time an Enterprise holds payments remitted by the seller/servicer 
before passing them through to the security investor.
    \38\ DCR is the ratio of property net income to debt service.
    \39\ Recourse refers to the sharing of credit risk with a 
seller/servicer; repurchase refers to the obligation of a seller/
servicer to repurchase 90-day delinquent loans.
---------------------------------------------------------------------------

b. Single Family Default and Prepayment
    The single family models are estimated using historical data on the 
performance of Enterprise loans through 1995. To simulate defaults and 
prepayments, the stress test uses a 30-year fixed-rate loan model, an 
adjustable-rate loan (ARM) model, and a third model for other products, 
such as 15-year loans and balloon loans. Each of the three single 
family models was separately estimated based on data for the relevant 
product types. Each includes a calibration adjustment, so that the 
results properly reflect a relationship to the benchmark loss 
experience, as described earlier.
    All three single family models simulate defaults and prepayments 
based on values for interest rates and property values, as described 
above, and variables capturing the risk characteristics of loan groups. 
The variables described below are the factors used to determine the 
rates of default and/or prepayment for single family loan groups:
     Mortgage Age--Patterns of mortgage default and prepayment 
have characteristic age profiles; defaults and prepayments increase 
during the first years following loan origination, and then peak 
between the fourth and seventh years.
     Probability of Negative Borrower Equity--Borrowers whose 
current loan balance is greater than the current value of their 
mortgaged property (reflecting negative equity) are more likely to 
default than those with positive equity in their properties. The 
probability of negative borrower equity within a loan group is a 
function of (1) house price changes (based on the HPI), and 
amortization of loan principal, which together establish the average 
current LTV, and (2) the dispersion of actual house price changes 
around the HPI value. Thus, even when the average current LTV for a 
loan group is less than one (positive equity), some percentage of the 
loans will have LTVs greater than one (negative equity).
     Relative Spread--This variable is an important factor in 
determining whether a borrower will prepay. It reflects the value to a 
borrower of the option to prepay and refinance. The stress test uses 
the relative spread between the interest rate on a loan and the current 
market rate on loans as a proxy for the mortgage premium value.
     Burnout--The value for this variable reflects whether a 
borrower has passed up earlier opportunities to refinance at favorable 
interest rates. Such a borrower is less likely to prepay the current 
loan and refinance, and more likely to default in the future.
     Yield Curve Slope--This variable reflects the relationship 
between short and long term interest rates. The shape of the yield 
curve, which reflects expectations for the future levels of interest 
rates, influences a borrower's decision to prepay a mortgage. Depending 
on the slope of the yield curve and the type of loan a borrower may 
have incentives to refinance to a fixed-rate or an adjustable-rate 
mortgage.
     Original LTV--The LTV at the time of mortgage origination 
serves as a proxy for factors relating to the financial status of a 
borrower, which can affect the borrower's future ability to make loan 
payments. Higher original LTVs, which generally reflect fewer economic 
resources and greater willingness to take financial risk, increase the 
probability of default and lower the probability of prepayment. The 
reverse is true for lower original LTVs.
     Occupancy Status--The value of this variable reflects the 
higher probability of default of investor-owners compared to that of 
occupant-owners. The stress test applies the portfolio-wide ratio of 
investor-to occupant-owners to each loan group. The single family 
default and prepayment variables are listed in Table 1.

[[Page 18093]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.186


c. Multifamily Default and Prepayment
    The stress test utilizes two multifamily default models and five 
multifamily prepayment models to capture the behavior of loans 
purchased under different programs and loans at different stages in 
their life cycles. The models were estimated using historical data 
through 1995 on the performance of Enterprise multifamily loans. The 
stress test applies one default model to loans purchased under cash 
programs (i.e., loans purchased individually), and another to loans 
purchased under negotiated programs (i.e., loans purchased as part of a 
pool), because the programs have different risk profiles. The 
prepayment models distinguish among product types: fully-amortizing 
fixed-rate, balloon, and ARM loans; those with yield maintenance 
provisions (i.e., restrictions and/or penalties for prepaying a loan 
during a specified period of time); and balloon loans which have 
reached their stated maturity, because these distinctions affect the 
probability of prepayment.
    As with the models of single family mortgage performance, the 
multifamily models simulate the probability of default and prepayment 
based on stress test conditions and loan group risk characteristics. To 
account for specific risks associated with multifamily loans, these 
loans are grouped somewhat differently from single family loans. Thus, 
multifamily loans are also grouped by original DCR and program type. 
All of the multifamily default and prepayment models include interest 
rates, rent growth rates, and vacancy rates to characterize stress test 
conditions.
    The following variables are factors in determining default and 
prepayment rates for multifamily loan groups:
     Mortgage Age--As with single family loans, the risk of 
default and prepayment on multifamily loans varies over their lives.
     Relative Spread--As with single family loans, this 
variable reflects the value to the borrower of the option to prepay and 
refinance.
     Program Restructuring--This variable captures the 
difference between Enterprises' management of their original 
multifamily programs and current, restructured programs. That 
difference affects the probability of default.
     Joint Probability of Negative Equity and Negative Cash 
Flow--This variable plays a role similar to that of the probability of 
negative equity for single family loans. However, negative equity is 
not a sufficient condition for multifamily loan default. Residential 
rental property owners tend not to default unless a property's net cash 
flow is negative as well. This variable captures the joint probability 
of both conditions.
     Balloon Maturity Risk--To reflect the added risk of 
default at the balloon maturity date, this variable gives extra weight 
to the joint probability of negative equity and negative cash flow in 
the year before a balloon mortgage matures.
     Default Type--This variable distinguishes between loans 
for which the Enterprise is responsible for foreclosure and property 
disposition and loans for which the seller/servicer is responsible for 
repurchasing if the loan becomes 90 days delinquent.
     Current LTV--This variable captures the incentive for 
borrowers to refinance in order to withdraw equity from their rental 
property.
     Probability of Qualifying for Refinance--This variable 
captures the effect on prepayments of a borrower who would not qualify 
for a new loan (one that lacks an LTV of 80 percent or less and a DCR 
of 120 percent or more).
     Pre-balloon Refinance Incentive--This variable gives extra 
weight to the relative spread in the two years prior to the balloon 
maturity. This captures the additional incentive to prepay balloon 
loans after the date the yield maintenance period ends, but before the 
balloon maturity date.
     Conventional Market Rate for Mortgages--Similar to the 
single family yield curve slope variable, this variable reflects the 
incentives for borrowers with ARMs to refinance into fixed-rate 
mortgages.
     Value of Depreciation Write-offs--This variable captures 
the effect on default rates of the value to a new purchaser of the tax 
benefits associated with multifamily property ownership.
     Years-To-Go in the Yield Maintenance Period--This variable 
captures the decreasing effect of yield maintenance provisions during 
the yield maintenance period. As the cost of the provision declines in 
the later years of the yield maintenance period, the disincentive to 
prepay declines.
    Just like the single family default and prepayment models, the 
multifamily models produce, for each loan group for each month of the 
stress period, default and prepayment rates which are used in the cash 
flow components of the stress test. Tables 2 and 3 list the variables 
included in the multifamily default and prepayment models.

[[Page 18094]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.187


[GRAPHIC] [TIFF OMITTED] TP13AP99.188

d. Loss Severity
    Credit losses are determined by multiplying default rates by loss 
severity rates and loan group balances. Loss severity rates are 
computed as of the date of default, and are expressed as a percentage 
of unpaid principal balance of the defaulting portion of a loan group.
    In general, losses comprise three elements--loss of principal, 
transactions costs, and funding costs. Loss of principal is the amount 
of defaulting loan UPB, offset by the net proceeds of the sale 
(disposition) of the foreclosed property. Transactions costs include

[[Page 18095]]

expenses related to foreclosure, property holding and disposition 
expenses. Funding costs are the costs of funding non-earning assets--
first the defaulted loans, and then the foreclosed properties prior to 
disposition (except in the case of sold loans, for which four months of 
interest at the passthrough rate replace four months of funding costs).
    For single family loans the stress test uses an econometric model 
to project the net proceeds from the sale of foreclosed properties. The 
model is based on historical data on defaulted Enterprise loans, and 
reflects the relationship between LTV at the time of loan default 
(based on a loan's original LTV, loan amortization, and house price 
changes and dispersion), and proceeds of property disposition. Just as 
with models of single family default and prepayment, this model 
includes a calibration adjustment to make the results consistent with 
the benchmark loss experience.
    For multifamily loans, sale proceeds are a fixed percentage of the 
defaulting UPB, based on historical experience.
    For both single family and multifamily loans, transactions costs 
are fixed amounts based on historical averages computed from Enterprise 
data. Funding costs are captured in a discounting process described in 
the following paragraph.
    Foreclosure, disposition and associated costs occur over a period 
of time. In order to calculate losses associated with a default as of 
the time of the default, the stress test calculates loss severity rates 
by discounting the different elements of loss back to the time of 
default, based on stress period interest rates. The discounting process 
also captures funding costs at appropriate interest rates. For single 
family loans, the timing of each element is based on averages for the 
benchmark loans; for multifamily loans it is based on the historical 
average for the Enterprises, using data through 1995.
    The calculation of loss severity rates for two types of multifamily 
loans differs from the general approach. In the case of 90-day 
delinquent loans that are repurchased from Enterprise security pools by 
seller/servicers, rates are a fixed amount based on Enterprise 
historical experience representing claims submitted by seller/servicers 
for reimbursement by the Enterprise. In the case of FHA-insured loans, 
the stress test reflects no losses.
    The loss severity component of the stress test generates loss 
severity rates for each loan group for each month of the stress period, 
which are used in the cash flow components of the stress test to 
calculate credit losses for the Enterprises.
5. Other Credit Factors
a. Mortgage Credit Enhancements
    In many cases, at least a portion of Enterprise losses on defaulted 
loans is offset by some form of credit enhancement. Credit enhancements 
are contractual arrangements with third parties that reduce Enterprise 
losses on defaulted loans. By including the effect of mortgage credit 
enhancements, the stress test more realistically reflects Enterprise 
risks related to mortgage defaults and credit losses during the stress 
period.
    The stress test captures many types of credit enhancements, with 
differing depths and methods of coverage, for both single family and 
multifamily loans. These credit enhancements include private mortgage 
insurance, recourse to seller/servicers, indemnification, pool 
insurance, cash accounts, spread accounts, collateral accounts, and 
specific risk-sharing agreements for certain multifamily loans.
    The stress test divides mortgage credit enhancements into two 
categories. One category is credit enhancements that cover losses on 
certain loans up to a specified percentage of the loss incurred. This 
category includes private mortgage insurance, unlimited recourse, 
unlimited indemnification and, for certain multifamily loans, risk-
sharing agreements. The other category includes those credit 
enhancements that cover all losses on a specified set of loans, up to a 
specified total amount. This category includes limited recourse, 
limited indemnification, pool insurance, cash accounts, spread accounts 
and collateral accounts.
    The benefits of the first category of credit enhancements are 
incorporated in the calculation of monthly loss severity rates. The 
loss severity rate for a specific loan group is reduced based on the 
credit enhancements from the first category associated with loans in 
that group. The benefits of the second category of credit enhancements 
are taken into account directly in the cash flow calculations. The 
dollar balance of these credit enhancements is tracked and drawn down 
to offset the amount of credit losses for the covered loans in a loan 
group.
b. Counterparty and Other Credit Risk
    In addition to mortgage credit quality, the stress test considers 
the creditworthiness of companies and financial instruments to which 
the Enterprises are exposed. These include most mortgage credit 
enhancement counterparties (e.g., private mortgage insurance companies 
and seller/servicers), privately issued and municipal securities held 
as assets, derivative counterparties, and securities guaranteed for 
private issuers.
    For credit enhancement counterparties, securities held as assets, 
and interest rate contract counterparties, the stress test reduces--or 
applies ``haircuts'' to--the amounts due from these instruments or 
counterparties according to their level of risk. The level of risk is 
determined by public credit ratings which the stress test classifies 
into four categories: AAA, AA, A and BBB. When no rating is available, 
the instrument or counterparty is rated BBB. The cash flow components 
of the stress test phase in the haircuts monthly in equal increments 
until the total reduction listed in Table 4 is reached in the final 
month of the stress period.

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[GRAPHIC] [TIFF OMITTED] TP13AP99.189


    The stress test also applies haircuts to reflect the impact of 
impairment of counterparties for derivative contracts hedging foreign 
currency denominated debt. Since counterparty impairment would reduce 
the effectiveness of a hedge, the stress test reflects the associated 
risk by increasing the amounts owed by an Enterprise by the haircut 
percentage.
c. Other Off-Balance Sheet Guarantees
    In addition to guaranteeing mortgage-backed securities they issue 
as part of their main business, the Enterprises occasionally provide 
guarantees for other securities. The guarantees provided by the 
Enterprises enhance the liquidity and appeal of these securities in the 
marketplace. These securities, notably single family and multifamily 
whole loan REMIC securities \40\ and mortgage tax-exempt multifamily 
housing bonds, represent a small part of the Enterprises' business and 
have a significant level of credit enhancement that protects the 
Enterprises from losses. The performance of these securities is not 
explicitly modeled in the stress test. As a proxy for the present value 
of net losses on these guarantees during the stress test, the 
outstanding balance of these instruments at the beginning of the stress 
period is multiplied by 45 basis points. The resulting amount is 
subtracted from the lowest discounted monthly capital balance when 
calculating the risk-based capital requirement.
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    \40\ Real Estate Mortgage Investment Conduit (REMIC) securities 
are multiclass mortgage passthrough securities. The classes of a 
REMIC security can take on a wide variety of attributes with regard 
to payment of principal and interest, cash flow timing 
(un)certainty, and maturity, among others.
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6. Cash Flows
    For each month of the stress period, stress test cash flow 
components apply projected default, prepayment, and loss severity rates 
to loan group balances to produce mortgage cash flows. The cash flow 
components also reduce projected mortgage losses resulting from 
offsetting credit enhancements that are not accounted for in loss 
severity calculations. In addition, the cash flow components calculate 
cash flows for securities that the Enterprises hold as assets, or have 
issued as liabilities. They generate cash flows for derivative 
instruments like interest rate swaps, caps, and floors; and they apply 
the haircuts to cash flows to reflect the credit risk of securities and 
counterparties other than mortgage borrowers. Projected cash flows are 
the principal inputs in the creation of monthly financial statements 
during the stress period, which are, in turn, the basis for the 
calculation of the risk-based capital requirement.
    Cash flows are generated for each single family and multifamily 
loan group. For retained loans, cash flows consist of scheduled 
principal, prepaid principal, defaulted principal, default losses, and 
interest. For sold loans, cash flows consist of credit losses, 
guarantee fee income, and float income.
    Because losses on sold loans are absorbed by the Enterprises and 
are not passed through to security holders, no credit losses are 
reflected in cash flows calculated for Enterprise-issued MBS held as 
investments (including those issued by an Enterprise and later 
repurchased). The credit risk is borne by the MBS issuer rather than 
the MBS investor, so the credit risk on MBS has already been taken into 
account in the credit risk of sold loans. Thus, cash flows for single 
class Enterprise-issued MBS held as investments consist only of 
principal and interest payments. Cashflows for private label securities 
consist of principal and interest payments and credit losses.\41\ 
Principal payments are calculated by applying default and prepayment 
rates that are appropriate for the loans underlying the MBS (amounts of 
defaulted principal are assumed to be passed through to investors, as 
well as normal amortization). Interest is computed by multiplying the 
security principal balance by the coupon rate.
---------------------------------------------------------------------------

    \41\ See section II. A. 5. c., Other Off-Balance Sheet 
Guarantees for a description of how credit losses for private label 
securities are calculated.
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    Multi-class mortgage securities such as REMICs and strips are 
treated in the same manner as single class MBS. The stress test 
generates cash flows for the underlying collateral, usually single 
class MBS, and applies the rules of the particular multi-class security 
that govern how these cash flows are directed to determine cash flows 
of the specific securities held by an Enterprise. In generating cash 
flows for mortgage-linked derivative contracts, where the notional 
amount of the contract is based on the declining principal balance of 
specified MBS, the stress test applies the terms of each contract and 
tracks the appropriate declining balances. The stress test generates 
cash flows for mortgage revenue bonds by treating the bonds like single 
class MBS backed by 30-year, fixed-rate single family mortgages 
maturing on each bond's stated maturity date.
    For non-mortgage investments, outstanding debt securities and 
liability-linked derivative contracts, payments of principal and 
interest are calculated for each instrument based on its

[[Page 18097]]

characteristics by applying the appropriate interest rates and 
principal payment rules. For asset-backed securities, one of two 
collateral prepayment speeds is applied, depending on the stress test 
interest rate scenario. The stress test computes cash flows for debt 
securities and liability-linked derivatives according to the rules and 
structure of each instrument.
7. Enterprise Operations & Taxes
    The stress test simulates the income taxes, operating expenses, 
issuance of new debt or purchase of new investments, exercise of 
options to retire debt early or cancel derivative contracts, and 
payment of dividends by the Enterprises. The stress test computes 
Federal income taxes using an effective tax rate of 30 percent. 
Estimated income tax is paid by the Enterprises quarterly.
    An Enterprise's operating expenses decline in proportion to the 
change in the size of its combined mortgage portfolio of retained and 
sold loans during the stress period. The baseline level of monthly 
operating expenses at the start of the stress period is equal to one-
third of operating expenses reported by the Enterprise for the quarter 
preceding the stress period.
    When necessary, the stress test simulates the issuance of new debt 
or purchase of new investments by the Enterprises. New debt is issued 
in months when there is a shortfall of cash. All debt issued during the 
stress period is six-month discount notes, at Enterprise borrowing 
rates projected from the estimated yield curve. Excess cash is invested 
in one-month securities bearing the six-month Treasury yield.
    For each month during the stress period that a security is subject 
to early redemption (call) or a derivative contract is subject to 
cancellation, the stress test calculates the effective remaining yield-
to-maturity \42\ of that instrument and compares it to the yield of a 
replacement security, given current stress period interest rates. If 
the yield is more than 50 basis points below the cost of the existing 
instrument, the call or cancellation option is exercised.
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    \42\ Yields are calculated based on the outstanding principal 
balances for securities and notional amounts for derivative 
contracts.
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    Capital distributions are also made during the stress period. If an 
Enterprise's capital exceeds the minimum capital requirement in any 
quarter, dividends on preferred stock are paid, unless payment would 
reduce the Enterprise's capital to an amount below the minimum 
requirement. Common stock dividends are paid only in the first four 
quarters of the stress period (based on an estimate of how long capital 
would remain above the risk-based requirement), and only if capital 
remains above the minimum capital requirement before and after the 
dividends are paid. The amount paid is directly related to the earnings 
trend of the Enterprise. If the trend is positive, the dividend payout 
ratio is the same as the average of the four quarters preceding the 
stress test. Otherwise, dividends are based on the dollar amount per 
share paid in the last quarter preceding the stress test. The stress 
test does not provide for any other capital distributions, such as 
repurchases of common stock.
8. Financial Reporting
    To the extent applicable, the stress test makes use of Generally 
Accepted Accounting Principles (GAAP). The cash flows from the 
financial instruments on the books of the Enterprises are the principal 
basis for the creation of pro forma financial statements that capture 
an Enterprise's performance over the stress period. In addition, the 
stress test accounts for numerous non-cash items on the Enterprises' 
balance sheets, such as receivables and unamortized and deferred 
balances. The balance sheets show the monthly total capital amount for 
each Enterprise, which is used in the final calculation of risk-based 
capital.
9. Calculation of the Risk-based Capital Requirement
    The stress test determines the amount of capital that an Enterprise 
must hold at the start date in order to maintain positive capital 
throughout the ten-year stress period (stress test capital). Once 
stress test capital has been calculated, an additional 30 percent of 
that amount is added to protect against management and operations risk. 
This total is the risk-based capital requirement.
    Using the financial statements generated by the stress test, the 
capital balance for each month is discounted back to the start of the 
stress period. This is done for both the up-rate and down-rate 
scenarios. The lowest discounted monthly capital balance is then 
decreased as described above to account for securities that are 
guaranteed by the Enterprises which are not explicitly modeled (other 
off-balance sheet guarantees). This lowest discounted monthly balance, 
if positive, represents a surplus of initial capital, that is, capital 
that was not ``used'' during the stress period. If negative, it 
represents a deficit of initial capital. The lowest discounted monthly 
balance is then subtracted from the Enterprise's initial capital. The 
resulting amount is the smallest amount of starting capital required to 
maintain positive capital throughout the stress period.
    For example, if an Enterprise holds starting capital of $10 billion 
and the lowest discounted monthly balance is $1 billion (representing a 
positive capital balance even in the worst month of the stress period), 
then the amount of starting capital necessary to maintain positive 
capital throughout the stress period is $9.0 billion. If the lowest 
discounted monthly balance is -$1 billion (representing a negative 
capital balance in the worst month), the necessary starting capital is 
$11.0 billion.
    In the final step, necessary starting capital is multiplied by 1.3 
to complete the calculation of the risk-based capital requirement 
required by the 1992 Act.

B. Sensitivity of Capital Requirement to Risk

    An Enterprise's risk-based capital requirement under this proposed 
regulation is sensitive to a wide variety of factors that affect 
Enterprise risk. The existing minimum capital requirement depends 
almost entirely on the size of an Enterprise's two principal 
businesses: MBS guarantees and leveraged investments in mortgages and 
in MBS. In contrast, the risk-based capital requirement depends not 
only on the outstanding volumes of an Enterprise's guarantees and 
assets, but also on the degree of risk taken on by the Enterprise in 
connection with these businesses. Thus, the risk-based requirement is 
sensitive to the characteristics of mortgages and mortgage guarantees 
that affect risk, credit enhancements for those mortgages, the asset/
liability risk management strategies of the Enterprise, the value of 
properties collateralizing the mortgages, and recent interest rate 
levels.
    In designing the stress test on which the risk-based capital 
requirement is based, OFHEO sought to incorporate all significant 
sources of credit and interest rate risk. OFHEO further sought to 
design the stress test so that differences in specific risk factors 
affect the risk-based capital requirement in amounts commensurate with 
the difference in risk. To quantify the marginal effects of changes in 
risk on the capital required for each scenario (required capital), 
OFHEO conducted a number of sensitivity tests. OFHEO first computed the 
risk-based capital requirement for each Enterprise in each interest 
rate

[[Page 18098]]

scenario for June 30, 1997.\43\ These results serve as a base case. 
OFHEO then made a series of small adjustments to each Enterprise's risk 
positions and compared the results for all four Enterprise-scenario 
combinations with the relevant base case results. The differences in 
results provide a measure of the incremental changes in required 
capital (which may be positive or negative) caused by the risk 
adjustment.
---------------------------------------------------------------------------

    \43\ The results are discussed in section II. C., Implications 
of the Proposed Rule.
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    Section II. B.1., MBS Guarantees (Sold Loans), below presents the 
results of sensitivity tests related to an Enterprise's guarantee 
business. In each test, OFHEO simulated the effects on required capital 
of a hypothetical addition to each Enterprise's outstanding MBS 
guarantees (sold loans). The simulation results show, in both an 
absolute and relative sense, how different characteristics of sold 
loans affect required capital. Section II. B. 2., Commitments, 
illustrates how required capital would be affected if each Enterprise 
had had a larger volume of outstanding commitments. Section II. B. 3., 
Assets and Liabilities, discusses the effects of hypothetical additions 
of retained loans accompanied by additions of debt. Section II. B. 4., 
Administrative Costs, discusses how risk-based capital would be 
affected by higher administrative (operating) expenses. Finally, 
Section II. B. 5., External Economic Conditions, discusses how risk-
based capital would be affected had house prices or interest rates 
behaved differently than they actually did in the period just preceding 
the starting date of the stress test.
    Sensitivity test results differ between the two Enterprises for two 
reasons. First, the risk adjustments made to the two Enterprises' 
positions were not precisely the same. For example, in sensitivity 
tests involving changes in outstanding sold loan volumes, each 
Enterprise's additional sold loans reflect that Enterprise's typical 
security remittance cycles, and remittance cycles affect the risk 
characteristics of sold loans. Second, the incremental effects on 
required capital of any change in an Enterprises's risk positions are 
affected by the Enterprise's individual circumstances and policies. Two 
examples are the Enterprise's projected Federal income tax situation 
during the stress period and its dividend policies. During portions of 
the stress period in which an Enterprise is paying taxes or receiving 
refunds, financial gains and losses are shared with the government 
because changes in income cause changes in taxes. Conversely, during 
portions of the stress period in which an Enterprise has exhausted tax 
carrybacks, the full benefit or cost of a change in income is 
experienced by the Enterprise. In the base case, both Enterprises 
exhaust their tax carrybacks mid-way through the stress period in the 
down-rate scenario. In the up-rate scenarios, Fannie Mae does the same, 
but Freddie Mac either pays taxes or receives refunds throughout the 
stress period. An Enterprise's tax situation during the stress period 
depends primarily on the Enterprise's risk exposures. The longer an 
Enterprise continues to be profitable in the stress environment, the 
longer it is affected by taxes.
    Differences in recent dividend policies can cause small differences 
in the incremental capital associated with specific changes in risk 
because common stock dividends during the first year of the stress 
period depend on recent dividend payouts. Differences in dividend 
policies, therefore, can lead to differences in the amount of earnings 
changes that are shared with stockholders.
    Results are shown for both interest rate scenarios, even though 
only one (the one that results in the highest required capital) can be 
binding at any specific time. For June 1997, the up-rate scenario 
resulted in higher required capital for Fannie Mae, while the down-rate 
scenario was more adverse for Freddie Mac. However, the relative 
adversity of the two scenarios may change over time for either 
Enterprise depending on business strategies and market conditions.
    In the tables of this section, the phrase ``incremental capital'' 
is used to mean the change in the amount of required capital in a 
particular scenario accompanying a small change in the overall risk 
profile of an Enterprise. Several considerations affect appropriate 
interpretation of these numbers. First, the incremental capital 
percentages shown in the tables are not fixed. As discussed below in 
section II. B. 5. c., Sensitivity to Risk Characteristics in Different 
Economic Environments, future business strategies and economic 
conditions may alter the required capital sensitivities from those of 
June 1997, which are presented here. Furthermore, bigger or smaller 
changes in risk may not have a proportional effect on capital. A $20 
billion increase in a particular group of loan guarantees may not have 
exactly twice the effect on required capital as a $10 billion increase 
in the same group of guarantees.
    Second, in anticipating the effect on required capital of a change 
in any risk factor, an Enterprise likely will be concerned not only 
with the immediate effect, but also with the longer term effect. For 
example, in considering the capital implications of making additional 
mortgage guarantees, the incremental effects on required capital of the 
guarantees at all future dates that the loans continue to be 
outstanding are relevant. In this case, an important consideration is 
that the incremental effects of mortgage guarantees generally diminish 
over time.
    Third, the incremental capital percentages do not determine an 
amount of capital that must be added in order to accept a specific 
increase in risk. As discussed below in Section II. C. 2., Enterprise 
Adjustments to Meet the Proposed Standard, it may often be less costly 
to increase hedges of other risks than to raise equity funds in 
response to an increase in risks.
1. MBS Guarantees (Sold Loans)
    The Enterprises have two principal lines of business. They function 
both as guarantors of mortgage-backed securities and as leveraged 
investors in mortgages and mortgage-backed securities. As guarantors, 
the Enterprises receive principal and interest payments on home 
mortgages, which they pass through to security investors, minus a share 
of the interest payments, which they retain as a guarantee fee. Because 
of differences in the timing of their receipt of funds and payments to 
investors, they also earn float income (which may be positive or 
negative). In return, they bear the risk of loss if a borrower 
defaults, and they incur additional administrative expenses.
    The stress test projects the flows of income and expenses 
associated with loan guarantees based on the characteristics of the 
mortgages and the economic circumstances of the stress period. The 
resulting net cash inflows or outflows are directly reflected in the 
Enterprise's borrowing or investing volumes during the stress period. 
The interest paid or received on the new debt issues or investments 
that are attributable to the guarantees have further effects on income, 
borrowing, and investing volumes. Income, in turn, affects taxes, 
dividends, capital, and (ultimately) required capital.
    OFHEO examined the implications for required capital of risk 
factors associated with sold loans as follows. After computing the 
capital required under this proposed rule for data reflecting the 
Enterprises' books of business and the accompanying economic 
circumstances as of June 30, 1997, OFHEO added a quantity ($10 billion) 
of sold loans that embodied the specific risk characteristics under

[[Page 18099]]

examination. The capital required for each scenario was then recomputed 
and compared with the capital required for the same scenario before 
loans were added. The difference is the incremental capital required 
for the additional sold loans in that scenario. The results are 
expressed as a percent of the volume of sold loans added.
    Additional sold loans would normally be accompanied by additional 
administrative expenses. In computing required capital for books-of-
business that included additional sold loans, OFHEO estimated the 
additional costs by increasing administrative expense for each 
Enterprise in proportion to the increase in that Enterprise's overall 
(retained plus sold loan) portfolio. Those costs amounted to about six 
basis points (0.06 percent) per year on the new sold loans for each 
Enterprise. Different assumptions about administrative costs would 
affect the results; Section II. B. 4., Administrative Costs, discusses 
the effects on required capital of differences in administrative costs.
    Section II. B. 1. a., Loans with Mixed Characteristics Reflecting 
Enterprise Portfolios, discusses a simulation incorporating a general 
increase in sold loans embodying the same mix of characteristics as 
that found in each Enterprise's sold loan portfolio in June 1997 and 
describes how the increase affects various types of income and expense 
over the course of the stress period. Section II. B. 1. b., Loans with 
Specific Identical Characteristics, discusses a series of simulations, 
each incorporating an increase in sold loans with specific 
characteristics.
a. Loans with Mixed Characteristics Reflecting Enterprise Portfolios
    The first simulation (Simulation 1) was designed to examine the 
incremental effects of a general increase in each Enterprise's sold 
loan portfolio (MBS guarantees). The volume of each loan group 
(comprising loans with a common set of risk factors) in each 
Enterprise's sold loan portfolio as of June 1997 was increased 
proportionally by a factor that resulted in a total of $10 billion of 
additional sold loans. The results indicate the effects on risk-based 
capital of a general expansion of an Enterprise's MBS guarantee 
business. Alternatively, they can be viewed as the average effect on 
required capital of sold loans, weighted by each Enterprise's mix of 
outstanding sold loan business in June 1997. The results, expressed as 
a percent of the increase in sold loans, are summarized in Table 5.
[GRAPHIC] [TIFF OMITTED] TP13AP99.190

    In the up-rate scenario, a general increase in sold loans has only 
a small effect on required capital for either Enterprise. For Freddie 
Mac, sold loans are, on balance, a small source of strength. That is, 
income generated over the course of the stress period by sold loans 
(principally guarantee fees and float) exceeds related expenses 
(principally loan losses and administrative expense). The reverse is 
true for Fannie Mae. In the down-rate scenario, the incremental capital 
required for these sold loan mixes is near 0.85 percent of the increase 
in guarantees for both Enterprises. On average, the results for the two 
scenarios are similar to the existing minimum capital ratios for sold 
loans of 0.45 percent.
    Table 6 illustrates the effects on specific income and expense 
categories of the additional sold loans in Simulation 1, and how these 
effects translate into changes in capital requirements.

[[Page 18100]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.191


    Guarantee fees and administrative expense depend on the volume of 
loans outstanding. Thus, they are sensitive to the projected 
liquidation rates (the sum of prepayment, default, and amortization 
rates) of the additional sold loans. In the down-rate scenario (with a 
ten-year constant maturity treasury yield of 3.2 percent during the 
last nine years of the stress period), loans prepay rapidly, while in 
the up-rate scenario (with all treasury yields at 11.4 percent), loans 
prepay slowly. As a result, in the up-rate scenario, guarantee fee 
income and administrative expense are roughly 2\2/3\ times as great as 
they are in the down-rate scenario.
    Credit losses (charge-offs) depend on the credit risk 
characteristics of the additional sold loans. They are also larger in 
the up-rate scenario than in the down-rate scenario because loans 
remain outstanding longer, and therefore, at risk of default. Loss 
severity rates also are higher in the up-rate scenario because the 
interest carrying cost on foreclosed real estate is higher. These 
differences between the two scenarios are moderated by somewhat more 
favorable house price behavior and by better average loan quality when 
interest rates are high. Loan quality is poorer when interest rates are 
low because the better quality loans are projected to prepay much 
faster. Because of these offsetting influences, credit losses in the 
up-rate scenario are only 1\1/3\ times as great as they are in the 
down-rate scenario. Freddie Mac's credit losses are about ten percent 
lower than Fannie Mae's, reflecting a slightly less risky mix of loan 
characteristics.
    Float income depends on security remittance cycles, interest rates, 
and loan liquidation rates. This source of income on the additional 
sold loans is higher, for both Enterprises, in the scenario with higher 
interest rates because of lower liquidation rates and higher earnings 
ratios on positive float balances. The difference is much more 
pronounced for Freddie Mac because of differences in security 
remittance cycles. Freddie Mac holds prepayment funds for a longer 
period than Fannie Mae, earning a market rate of interest during the 
extra time, while accruing liabilities to investors at the security 
coupon rate. When interest rates rise, that provides extra income, but 
when rates fall, net losses accrue.
    Net interest income is affected because net cash inflows and 
outflows associated with the other income and expense categories lead 
to changes in borrowing or investing. The effects are small in the up-
rate scenario because the net flows caused by other factors are small. 
The effects also are small in the down-rate scenario, even though the 
net cash flows are much larger, because the interest rates associated 
with new borrowing or investing are low.
    Taxes reduce the effects of all income changes by 30 percent as 
long as an Enterprise is paying taxes or receiving tax refunds. Because 
both Enterprises, in the decreasing interest rate environment, and 
Fannie Mae, in the increasing rate environment, exhaust their tax 
carrybacks mid-way through the stress period, the tax effects vary 
depending on the timing of income flows during the stress period. 
Freddie Mac, however, performs well in the up-rate scenario, given its 
June 1997 risk positions, and pays taxes or receives refunds throughout 
the stress period.

[[Page 18101]]

    Dividends on common stock can be affected by additional sold loans 
only through changes in income during the first year of the stress 
period because the stress test specifies that common stock dividends 
are paid only during that year. Common stock dividends are little 
affected in this simulation because income changes during the first 
year are small and because dividends in the base case simulations for 
Fannie Mae in both scenarios, and Freddie Mac in the down-rate 
scenario, are insensitive to income. In those cases, dividends are set 
at their absolute level in the quarter preceding the stress test 
because of income declines during the first year. Preferred stock 
dividends are unaffected in this simulation because the changes in 
capital are insufficient to affect whether either Enterprise meets its 
minimum capital requirement during the stress period.
    The total change in capital is the sum (using the appropriate 
signs) of the effects measured through all of the above income and 
expense categories. The sum equals the net decline in capital at the 
end of the stress period (as a percent of the increase in sold loans). 
The capital position in the final month of the stress period is the 
lowest during the stress period for both Enterprises in both scenarios 
for the June 1997 base case, so it is the basis for the required 
capital calculations in all of the simulations discussed in this 
section.
    The cumulative discount factor is based on after-tax borrowing or 
investing interest rates. Thus, discount factors are relatively high in 
the up-rate scenario. Freddie Mac's discount factor is lower than 
Fannie Mae's in that scenario because taxes reduce Freddie Mac's after-
tax interest rates in the second half of the stress period, but do not 
reduce Fannie Mae's. The discounted total shows the effects of the 
additional sold loans on the amount of capital needed to survive the 
stress test. This amount, when multiplied by 1.3 to include the 
additional amount for management and operations risks, shows the 
effects on required capital of the additional sold loans.
b. Loans with Specific Identical Characteristics
    Unlike the first simulation, which showed the combined effects of 
each Enterprise's existing mix of risk factors, the following 
simulations focus on the effects of changes in specific risk factors. 
In each of the following cases, the sold portfolio is increased as 
before, but all of the additional loans are identical. The results show 
how much required capital would be affected by additional sold loans 
with specific risk characteristics and guarantee fees or, 
alternatively, how much loans with such characteristics and fees 
contribute to required capital. The assumptions about guarantee fees 
have a significant effect on the results. Guarantee fees are generally 
the same in most of these simulations in order to focus the results on 
the incremental capital effects of specific risk factors. In practice, 
though, the Enterprises typically vary the guarantee fees charged to a 
loan seller depending on the mix of loans they receive from that 
seller. Thus, the Enterprises implicitly charge higher fees for riskier 
loans. It would be misleading to characterize these simulation results, 
which are based on constant guarantee fees, as indicating the relative 
capital implications of loans in different risk groups as typically 
acquired by the Enterprises, without making an appropriate adjustment 
for typical differences in effective guarantee fees. Making such an 
adjustment in the model would be difficult, however, because the 
Enterprises do not generally make explicit differences in guarantee 
fees for individual loans with differences in risk. The same guarantee 
fee typically applies to all loans in a pool of loans and may be 
affected by the mix of loans in the pool.
    Also, Enterprise guarantee fees remain constant over the life of 
the loan, but the risk of the loan generally declines as the loan 
seasons. A majority of the simulations in this subsection involve new 
loans. The comparative results of such simulations provide a measure of 
the relative effects on required capital of different risk factors, but 
these results do not, by themselves, indicate the expected effects on 
required capital of the loans over their lifetimes. Additional 
simulations show the effects of loan seasoning on required capital.
    In these simulations, securities were assumed to have been sold at 
par with coupons equal to the contract interest rates, less the 
servicing and guarantee margins. Servicing margins are 30 basis points. 
For Fannie Mae, the loans were assumed to be securitized under their 
standard programs with seven days of float on passthrough payments. For 
Freddie Mac, their ``45-day'' security rules were assumed in float 
calculations. These securities have negative three days of float on 
scheduled principal and interest (payments are made to investors before 
payments are received from servicers) and an average of 38 days of 
float on prepayments. (In Simulation 1, both 45-day and 75-day rules 
were used for Freddie Mac, based on the mix of securities outstanding 
in June 1997.)
(i) Differences in Guarantee Fees
    To illustrate the effect on required capital of guarantee fees, two 
simulations were performed that were identical except for guarantee 
fees. In Simulations 2 and 3, shown in Table 7, the additional sold 
loans were all newly originated, fixed-rate mortgages (FRMs) in the 
West South Central Census Division (Texas, Oklahoma, Louisiana, and 
Arkansas); with 30-year terms, 7.5 percent contract interest rates, and 
80 percent loan-to-value ratios (LTVs). In Simulation 2, guarantee fees 
were set at 23 basis points, which is roughly the overall average rate 
for the two Enterprises, but not necessarily for loans with these 
characteristics. This simulation is used as a reference for comparison 
in Tables 8, 11, 12, 16, 17, 19, and 20. The average rate was used in 
most of the simulations involving additional single family loans for 
convenience and to isolate the differential effects of other risk 
factors. In Simulation 3, however, the guarantee fee was reduced to 18 
basis points to isolate the effects of different guarantee fees. The 
differences in the results for Simulations 2 and 3 can be used to 
roughly estimate how the results of other simulations might have been 
affected by other guarantee fee assumptions.

[[Page 18102]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.192


    The incremental capital needed for loans in both of these 
simulations is substantially higher than that needed for loans with the 
mix of characteristics in Simulation 1. This result occurs mainly 
because new 30-year FRMs have nearly double the credit losses in the 
up-rate scenario and 50 percent more in the down-rate scenario. For 
Freddie Mac, an additional reason is that securities with the 45-day 
remittance cycle assumed in Simulations 2 and 3 produce substantially 
less float income in the up-rate scenario and more negative float 
income in the down-rate scenario than the average guarantee mix in 
Simulation 1 did. Freddie Mac's capital need in the up-rate scenario is 
reduced relative to Fannie Mae's because of tax effects in the second 
half of the stress period.
    The effect of lower guarantee fees is to increase required capital 
in both scenarios. A five basis-point reduction in guarantee fees 
raises required capital by 14 to 18 basis points in the down-rate 
scenario. The difference in incremental capital is twice that amount in 
the up-rate scenario because the loans survive longer, owing to 
significantly fewer prepayments, and so the change in the fee rate 
applies to a larger volume of outstanding loans during the stress 
period.
(ii) Differences in Loan Age, With Slow and Steady House Price 
Inflation
    Seasoned loans (those not recently originated) have different risk 
characteristics than new loans because loans have different 
propensities to default and prepay at different ages and because the 
houses collateralizing seasoned loans have experienced changes in 
value. Changes in house value alter the probability of negative 
borrower equity, a key factor influencing default behavior.
    In Table 8, the results of Simulations 4-7, along with Simulation 
2, which is repeated here, show the effects of age on risk for loans 
originated in the West South Central Census Division. Houses in that 
area of the country generally have experienced price appreciation near 
the national average in recent years. Average annual appreciation over 
the eight years ending in the second quarter of 1997 was 3.0 percent. 
Table 9 shows the cumulative average appreciation for houses 
collateralizing loans of different ages.
[GRAPHIC] [TIFF OMITTED] TP13AP99.193

    All of the simulations reported in Table 8 are identical, except 
for the age of the sold loans underlying the additional guarantees. 
Given the steady increase in house prices preceding the starting point 
of the simulations, loans are less likely to default over the course of 
the stress period the older they are at the beginning of the period. 
Cumulative credit losses for loans made eight years before the start of 
the stress period are only about \1/5\ as great as for new loans in the 
up-rate scenario, and about \2/5\ as great in the down-rate scenario. 
In addition, loans made more than four years earlier have lower 
liquidation rates than new loans, providing a larger stream of 
guarantee fees. Consequently, guarantees of older loans cause much 
smaller increases in capital requirements in the down-rate scenario and 
actually reduce capital required in the up-rate scenario.

[[Page 18103]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.194


(iii) Differences in Past House Price Appreciation
    The benefits of loan age in reducing risk can be substantially 
increased or reversed by differences in house price appreciation. Table 
10 shows results for simulations on four-and eight-year-old loans from 
different geographic areas. Simulations 8 and 9 are the same as 
Simulation 5, except the loans in Simulation 8 were made on properties 
in the Mountain Census Division, where house values rose sharply after 
the loans were originated, and loans in Simulation 9 were made in the 
Pacific Census Division, where house values were stagnant. Similarly, 
Simulations 10 and 11 are the same as Simulation 7, except for the 
Census division.
[GRAPHIC] [TIFF OMITTED] TP13AP99.195

    For four-year-old loans, differences in credit losses are 
substantial and account for almost all differences in results. In both 
scenarios, credit losses are more than 2\1/2\ times as great in the 
Pacific Census Division as they are in the Mountain Census Division. 
However, the effects of different previous changes in house prices 
ultimately diminish. For eight-year old loans, charge-offs are only 
about \1/3\ higher in the Pacific Census Division, despite increasing 
disparity in house price appreciation. Furthermore, that smaller 
proportional increase in charge-offs is applied to a smaller base 
because charge-offs are much lower for eight-year old loans than for 
four-year old loans in all three Census divisions.
(iv) Differences in Loan Age and Loan-to-Value Ratio
    The higher the original loan-to-value ratio of a loan, the lower 
the borrower equity. Thus, the more likely it is to default and less 
likely it is to prepay. The effects of differences in original LTV, 
however, generally diminish with age. Table 11 shows the results for 
different LTV-age combinations for 30-year FRMs in the West South 
Central Division.

[[Page 18104]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.196


    In these simulations, the 95 percent LTV loans are assumed to be 
covered by private mortgage insurance with 30 percent coverage, the 
current Enterprise standard, provided by a double-A rated firm. Even 
with the insurance coverage, however, high LTV loans are much riskier 
than low LTV loans. Not only are high LTV loans more likely to default 
at any time during the stress period, but they are also less likely to 
prepay, especially in the down-rate scenario. Thus, they are exposed to 
default risk over a longer amount of time.
    For newly originated loans, the results are particularly striking. 
In the up-rate scenario, credit losses on 95 percent LTV loans are very 
much higher than they are for 50 percent LTV loans. In the down-rate 
scenario, the difference is even greater. These differences in 
performance between high and low LTV loans are much bigger than would 
be expected in normal times. But the very poor credit conditions in the 
stress test environment have a disproportionate effect on the more 
vulnerable high LTV loans.
    For seasoned loans, the effects of LTV are muted. Seasoned loans 
with 50 percent LTVs reduce required capital less than comparable new 
loans. Though credit losses are lower than those of newly originated 
loans, the difference is minor, as credit losses are very low in both 
cases. More importantly, the older loans amortize faster, reducing 
guarantee fees significantly. For loans with 95 percent LTVs, the 
difference in credit losses between seasoned and new loans is 
substantial. With a 13.7 percent average house price appreciation since 
origination, these seasoned 95 percent LTV loans perform only a little 
bit worse than newly originated 80 percent LTV loans.
(v) Differences in Product Type and LTV Ratio
    The simulations shown in Table 12 show the relative effects of 
three different product types (30-year FRMs, 15-year FRMs, and 
adjustable-rate mortgages) with low, medium, and high LTVs). All are 
newly originated loans. To isolate the effects of loan type, the 7.5 
percent contract loan rate was retained for the 15-year FRMs and is the 
initial rate on the adjustable-rate mortgages (ARMs). The ARMs adjust 
annually to 2.75 percentage points above the one-year constant maturity 
Treasury yield, with a two percentage point annual adjustment cap and a 
five percentage point lifetime cap.

[[Page 18105]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.197


    The intermediate-term (15-year) FRMs have consistently lower credit 
losses than long-term (30-year) FRMs because the shorter-term loans 
amortize more quickly, and borrowers choosing those loans tend to have 
greater financial resources. For 50 percent LTV loans, the difference 
in credit losses is small, as credit losses are very low for loans of 
both terms. In the up-rate scenario, the 30-year loans benefit from 
slower amortization, which results in more guarantee fees. In both the 
80 percent and 95 percent LTV categories, the more favorable 
incremental capital effects of 15-year loans reflect their greater 
safety. For 95 percent LTV loans, the 15-year loans have sharply lower 
credit losses, nearly 90 percent below those of 30-year FRMs.
    ARM loans are riskier than 30-year FRMs at all LTV levels in the 
up-rate scenario, with the differences becoming more pronounced as LTV 
ratios rise. ARM credit losses in the up-rate scenario are only 
modestly higher than 30-year FRM credit losses for low LTV loans, but 
rise to more than double those for 30-year FRMs for high LTV loans. 
Credit losses for high LTV ARMs cumulate over the course of the stress 
period to 13.5 percent of the initial loan balances. As the loan 
interest rates adjust to their lifetime caps, some borrowers have 
difficulty meeting the elevated payments.
    When interest rates decline, ARMs perform much better. They prepay 
much more slowly than FRMs in this environment and, therefore, produce 
substantially more guarantee fee income. At low and moderate LTVs, ARMs 
have more favorable capital effects than FRMs. However, the greater 
sensitivity of defaults on ARMs with high initial LTVs outweighs the 
benefits of higher fee income generated by such loans. While credit 
losses for high LTV ARMs are still much lower in the down-rate scenario 
than in the up-rate scenario, the discounted values of those losses are 
larger in the down-rate scenario because the discount rates are so much 
lower in that scenario. The capital effects depend on the discounted 
values, so they are nearly as large in the down-rate scenario for high 
LTV ARMs as they are in the up-rate scenario. Because of the high risk 
associated with high LTV ARMs, the Enterprises generally have not 
purchased ARMs with LTV ratios above 90 percent under their regular 
underwriting guidelines.
(vi) Differences in Multifamily Loans
    The Enterprises deal in a large variety of multifamily loan 
products, and the products differ significantly between the 
Enterprises. The simulations reported in Table 13 show the incremental 
effects on required capital of multifamily loans with some relatively 
common characteristics. The additional sold loans in Simulation 22 are 
newly originated 15-year balloons with 70 percent LTVs, debt coverage 
ratios (DCR) of 1.3.\44\ The Fannie Mae loans are assumed to provide 
partial recourse to the seller for losses, while the Freddie Mac loans 
do not. Accordingly, a higher guarantee fee is assumed for Freddie Mac 
loans, 75 basis points, than for Fannie Mae loans, 50 basis points. 
Simulations 23, 24, and 25 differ, respectively, by changing the 
balloon to five years, changing the LTV to 80 percent and the DCR to 
1.2, and changing the loan age to five years.
---------------------------------------------------------------------------

    \44\ All of the multifamily loans were originated in the West 
Census Region with 8.5 percent coupons and servicing margins of 50 
basis points.

[[Page 18106]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.198


    Unlike single family loans, multifamily loans with a few years of 
seasoning have substantially higher credit losses during the stress 
period. Both types of loans generally have low credit losses in the 
first years after origination, then rise to a peak before declining. 
However, the peak loss years for multifamily loans come several years 
after those for single family loans. Thus, the five-year old loans in 
Simulation 25 experience more bad loss years than comparable new loans 
(Simulation 22). Credit losses for high LTV, low DCR loans (Simulation 
23) are also higher than comparable lower LTV, higher DCR loans because 
there is a higher probability that the borrower would have an economic 
incentive to default during the stress period (no equity and negative 
cash flow). Five-year balloons have higher losses in the up-rate 
scenario because some properties would be unable to manage the higher 
interest rates that would accompany a new loan. In the down-rate 
scenario, five-year balloons terminate sooner and, thus, provide less 
guarantee fee income.
    Multifamily loan losses are generally less than guarantee fee 
income in the down-rate scenario. This is especially true for newly 
originated loans because most of the loans prepay before reaching their 
peak loss years. Multifamily loans also benefit in the down-rate 
scenario from lower capitalization rates, which improve their estimated 
LTVs.
(vii) Differences in Mortgage Insurance on High LTV Loans
    By law, conventional loans purchased by the Enterprises with LTVs 
greater than 80 percent require credit enhancement. Of the three types 
permitted, private mortgage insurance is by far the most commonly used. 
As described above, simulations involving additional guarantees for 
loans with 95 percent LTV ratios assume that the loans carry 30 percent 
coverage by a AA rated firm. The simulations reported in Table 14 show 
effects of varying insurance characteristics on single family loans. 
The guarantee additions in each case are for newly originated, long-
term FRMs.
[GRAPHIC] [TIFF OMITTED] TP13AP99.199

    In 1995, both Enterprises raised their coverage requirements on 95 
percent LTV loans from 25 percent to 30 percent. Credit losses in 
Simulation 26, with lower coverage than in Simulation 13 (but with all 
other characteristics are the same), are 15 percent higher in the down-
rate scenario and 12 percent higher in the up-rate scenario than they 
are in Simulation 13. Because the discounted value of those changes is 
higher in the down-rate scenario, the

[[Page 18107]]

required capital is affected more significantly in that scenario. 
Reducing the credit quality of the coverage (Simulation 28) has much 
the same effect as reducing the amount of coverage, while improving the 
credit quality (Simulation 27) has the opposite effect.
(viii) Differences in Mortgage Interest Rates
    Loans with low interest rates amortize more quickly and prepay more 
slowly. The reverse is true for high interest rate loans. Table 15 
shows the results of simulations for newly originated, long-term FRMs 
with different interest rates. In practice, loans with different 
interest rates have been originated in different time periods. However, 
to isolate the effects of different mortgage interest rates, all loans 
are assumed to be made simultaneously.
[GRAPHIC] [TIFF OMITTED] TP13AP99.200

    Faster amortization improves loan quality, so credit losses are 
significantly lower for mortgages with low interest rates. Low interest 
rate loans also prepay significantly more slowly in the down-rate 
scenario, increasing guarantee fees. For Freddie Mac, these differences 
between high and low mortgage interest rates are accentuated by 
differences in float income. Freddie Mac holds prepayments for an extra 
month before passing them through to investors. During that month, 
Freddie Mac earns a market rate of return while paying investors at the 
mortgage security coupon rate. Float earnings are roughly the same for 
both high and low mortgage interest rates, but interest passthrough 
payments to investors are much lower on low rate mortgages, increasing 
net float income.
(ix) Differences Between Loans on Owner-Occupied and Investor-Owned 
Properties
    Loans on owner-occupied properties present less credit risk than 
loans on investor-owned properties. Simulation 31, presented in Table 
16, shows the effects on required capital of adding newly originated, 
long-term fixed-rate mortgages that are all investor-owned. Required 
capital for loans on investor-owned properties is substantially higher 
in all cases because of higher credit losses.
[GRAPHIC] [TIFF OMITTED] TP13AP99.201

2. Commitments
    While commitments to purchase mortgages may result in new mortgage 
guarantees or new retained mortgages, the risk accepted by the 
Enterprise at the time of commitment is comparable to the risk on new 
mortgage guarantees. The stress test treats mortgages delivered 
pursuant to commitments as guarantees of mortgages that are originated 
in the first few months of the stress test at market interest rates. 
Hence, no portfolio interest rate risk will be incurred. The mix of 
other characteristics of the loans reflects the mix of characteristics 
for existing guaranteed loans of the Enterprise that

[[Page 18108]]

were originated during the six months preceding the start of the stress 
period.
    Simulation 32, shown in Table 17, shows the effects on required 
capital of increasing each Enterprise's commitments outstanding in June 
1997 by $10 billion. The results are, essentially, an average of the 
effects on required capital of a mixture of new loans, in which the 
proportions of loans with particular characteristics (including 
guarantee fees) match those present in an Enterprise's recently 
originated and securitized loans. In the up-rate scenario, the effects 
are muted relative to those in the down-rate scenario because the model 
assumes that sellers deliver loans for only 75 percent of the 
commitment volumes.
[GRAPHIC] [TIFF OMITTED] TP13AP99.202

3. Assets and Liabilities
    The Enterprises' other line of business is purchasing mortgages and 
mortgage securities for their asset portfolios and funding them with 
debt. As holders of mortgages, the Enterprises receive interest income, 
incur administrative expenses, and bear the risk of loss if a borrower 
defaults. As market interest rates change, the interest rate of a 
mortgage becomes more or less favorable, and the value of the mortgage 
will change. The Enterprises hedge this risk by issuing callable long-
term debt, which changes in value in a corresponding way. They also 
enter into interest rate derivative contracts that further reduce the 
overall sensitivity of their income and net worth to interest rate 
changes. As a holder of mortgage securities, an Enterprise experiences 
cash flows, income, and risks similar to those experienced as a holder 
of whole mortgages except that the credit risk is borne by the security 
guarantor (usually the Enterprise itself, acting in its other principal 
role).
    The stress test projects the flows of income and expenses 
associated with these assets in much the same way as it does for 
mortgage guarantees. However, principal and interest received by an 
Enterprise on retained mortgages and mortgage securities is not passed 
on to investors, and no credit losses are charged on asset holdings of 
mortgage securities guaranteed by either Enterprise or by the 
Government National Mortgage Association (Ginnie Mae). In addition, the 
stress test projects interest expenses associated with debt and cash 
flows associated with derivatives contracts.
a. Assets/Liabilities With Mixed Characteristics Reflecting Enterprise 
Portfolios
    Table 18 shows the additional capital that would be required in 
both scenarios by a general increase in each Enterprise's assets and 
liabilities. It is not possible to isolate the average incremental 
capital effects of a general increase in an Enterprise's mortgage 
assets in the same way that Simulation 1 measured those effects for 
guaranteed mortgages. Critical factors in assessing the risk of asset 
positions are the characteristics of the debt and equity used to fund 
them. However, specific debt and equity issues cannot be matched with 
specific assets. It is possible, however, to obtain a measure of the 
incremental capital effects of a proportional $10 billion increase in 
all of an Enterprise's assets, including non-mortgage assets, and a 
simultaneous $10 billion increase in the Enterprise's liabilities and 
interest rate derivatives.\45\
---------------------------------------------------------------------------

    \45\ The process is indirect, using the results of other 
simulations. The increase in required capital for an equal 
percentage increase in all of an Enterprise's positions, such that 
assets increase by $10 billion, is simply that percentage of the 
Enterprise's required capital for the base case simulations for June 
1997. This increase includes increases in guarantees and 
commitments. The effect of these increases can be removed by 
subtracting the incremental effects of the guarantees and 
commitments as calculated in Simulations 1 and 32, after making 
adjustments for the differences between a $10 billion change in 
those factors and a change of the percentage amount used in the 
first step.
[GRAPHIC] [TIFF OMITTED] TP13AP99.203

    These results reflect some differences between the Enterprises in 
asset composition, but, mostly, differences in debt structure and 
derivatives use in June 1997. In three of the four cases, the 
incremental effects are close to or less

[[Page 18109]]

than the 2.50 percent minimum capital ratio for Enterprise assets. For 
both Enterprises, the incremental required capital effects of sold 
loans were higher in the down-rate scenario while the effects of asset 
holdings and liabilities are higher in the up-rate scenario. Thus, the 
combined risks of both types of activities are more balanced with 
respect to interest rates than the risks of either type separately.
b. Retained Loans With Specific Identical Risk Characteristics
    The simulations discussed below show the effect on required capital 
of an increase in mortgage assets that is funded by debt. A first group 
of simulations shows how different characteristics of mortgages affect 
required capital in each scenario. Five-year, fixed-rate notes were 
used to fund mortgage assets in each of these simulations. Different 
funding would not have an appreciable effect on the relative results 
for mortgages of differing characteristics, as long as the funding was 
the same for each. In the second group of simulations, mortgage 
characteristics were held constant, while the funding varied among 
three alternatives.
    The Enterprises have available, and utilize, a much wider range of 
funding alternatives than those used in these simulations. These 
alternatives include debt (both callable and non-callable) of different 
maturities, debt-derivative combinations that create synthetic debt 
with various maturity and call characteristics, and debt combined with 
swaptions (options on swaps) or with interest rate caps, floors, or 
corridors. Other hedging techniques, such as asset swaps, are also 
used. The proposed risk-based capital requirements are fully sensitive 
to all of these alternatives.
    In the Simulations presented in Table 19, $10 billion of retained 
unsecuritized loans with specific risk characteristics were added to 
each Enterprise's asset portfolio. The assets were funded with $10 
billion of five-year notes paying 6.5 percent interest, with no call 
options. The mortgages in Simulation 33 have the same characteristics 
as those in Simulation 2, except they have not been securitized. They 
are newly originated 30-year fixed-rate mortgages, with 80 percent LTV 
ratios and 7.5 percent contract interest rates from the West South 
Central Census Division. In Simulations 34 through 39, one risk 
characteristic (mortgage type, LTV, or age) has been changed from 
Simulation 29 to illustrate the relative effects on required capital of 
changes in various characteristics.\46\
---------------------------------------------------------------------------

    \46\ While these results are for additional retained whole 
loans, the effects on required capital of additional holdings of 
mortgage security assets, backed by loans with the same 
characteristics and funded with the same debt, can be closely 
approximated by subtracting the effects of additional guarantees of 
loans with those characteristics. (The comparable loan guarantee 
simulations are Simulations 2, 17, 20, 12, 13, 5, and 7 
respectively.)
[GRAPHIC] [TIFF OMITTED] TP13AP99.204

    As the results make clear, using solely five-year fixed-rate debt 
to fund mortgages would not be an appropriate funding strategy to guard 
against the risk of large, sustained changes in interest rates like 
those incorporated in the stress test. When market interest rates 
decline, fixed-rate mortgages prepay rapidly, and the five-year debt is 
outstanding far longer than most of the mortgages it originally funded. 
When market yields rise, fixed-rate mortgages prepay slowly, and the 
debt matures long before most of the mortgages are liquidated.
    In the up-rate scenario, ARMs with fixed-rate funding reduce 
required capital because interest income rises with market yields 
(until lifetime caps are reached), while funding costs remain unchanged 
during the first five years. Differences in the impact on required 
capital of fixed-rate mortgages of different types in the up-rate 
scenario primarily reflect differences in credit losses. However, 15-
year loans also benefit from faster amortization, making their loan 
lives correspond more closely to the maturity of the debt used to fund 
them.

[[Page 18110]]

    In the down-rate scenario, ARMs prepay more slowly than FRMs, but 
also provide lower interest income. Among fixed-rate types of loans, 
four-year-old loans prepay more rapidly than new or eight-year-old 
loans. High-LTV loans, on the other hand, prepay slowly because 
borrowers lack sufficient equity for refinancing. These differences in 
prepayment rates greatly affect the interest rate risk characteristics 
of the loans, so that if they are funded with the same liabilities, 
four-year old loans with 80 percent LTVs generate higher capital needs 
in down-rate scenario than new loans with 95 percent LTVs, despite much 
lower credit losses.
    The proposed capital requirements are very sensitive to differences 
in funding strategies for mortgage assets because of the magnitude of 
the interest rate changes in the two scenarios. Table 20 shows the 
results of three alternative funding choices for newly originated long-
term FRMs with 80 percent LTVs like those in Simulation 33.
[GRAPHIC] [TIFF OMITTED] TP13AP99.205

    Funding long-term FRMs with short-term debt (six-month discount 
notes) provides very substantial benefits when interest rates fall. The 
debt matures more rapidly than the mortgages, permitting an Enterprise 
to continue receiving the original yield on the mortgages, while paying 
much lower interest rates. Short-term funding, though, is extremely 
costly when interest rates rise because maturing debt must be replaced 
at much higher rates. A portfolio of long-term fixed-rate mortgages 
funded with short-term debt, such as those held by Fannie Mae and most 
thrifts in the late 1970s, would require a capital/asset ratio of well 
over 20 percent under the proposed rule.
    Funding with long-term debt (ten-year notes with semi-annual 
interest payments at 6\3/4\ percent) provides large benefits when 
interest rates rise, but is extremely costly when interest rates fall. 
Callable long-term debt (ten-year maturity, with a coupon of 7\3/8\ 
percent, not callable during the first two years) provides benefits in 
both scenarios.\47\ The results for different funding mixes can be 
approximated by combining the results shown in Table 20 on a weighted 
average basis. Thus, for example, in June 1997, the incremental capital 
effects of new fixed-rate mortgages funded with 65 percent callable 
long-term debt, 19 percent short-term debt, and 16 percent long-term, 
non-callable debt would be in a range of 1.2 percent to 2.6 percent for 
both Enterprises in both interest rate scenarios. Less callable debt 
would be needed to achieve the same result for seasoned loans.
---------------------------------------------------------------------------

    \47\ The interest rates of long-term debt used in the 
simulations roughly reflect what the average cost of such 
instruments would have been in June 1997.
---------------------------------------------------------------------------

4. Administrative Costs
    During the stress period, administrative costs depend not only on 
the volume of loans held or guaranteed, but also on the rate of 
spending in the quarter immediately preceding the start of the stress 
period. A higher rate of administrative expense before the stress 
period increases costs and depletes capital during the stress period. 
In Simulation 43, shown in Table 21, $10 million in annual 
administrative expense ($2.5 million at a quarterly rate) was added to 
each Enterprise's reported spending in the year preceding the date of 
the base case simulations (June 1997).
[GRAPHIC] [TIFF OMITTED] TP13AP99.206

    The results in Table 21 show that if Fannie Mae's annual 
administrative expense rate had been $1 higher in the year preceding 
the stress period, its capital requirement would have been $5.92 higher 
in the up-rate scenario and $3.53 higher in the down-rate scenario. The 
stress test projects the higher expense rate to continue throughout the

[[Page 18111]]

ten years of the stress period, except that the dollar amount of 
additional expense declines in line with the outstanding loan volume. 
Thus, in the up-rate scenario, for example, the initial annual $1 
increase in the expense rate leads to an additional $7.65 of 
administrative expenses during the stress period. Discounting, taxes, 
and dividends reduce the incremental required capital to $5.92, even 
after the 30 percent management and operations risk supplement. 
Required capital increases more in the up-rate scenario than the down-
rate scenario because administrative expense is tied in the stress test 
to outstanding loan volumes, which are larger in the up-rate scenario.
    The effect of increased administrative expenses on required capital 
is lower for Freddie Mac in both interest rate scenarios. This is true 
partly because Freddie Mac's mortgages have slightly shorter lives in 
both interest rate scenarios, but more importantly because Fannie Mae 
has disproportionately larger commitments outstanding at the start of 
the stress period. As commitments are transformed into loans during the 
early months of the stress period, Fannie Mae's overall loan balances 
rise relative to initial balances by more than Freddie Mac's. This 
effect is less significant in the up-rate scenario because only 75 
percent of commitments become loans. However, Freddie Mac's costs in 
the up-rate scenario are reduced by taxes throughout the stress period, 
while Fannie Mae's are not. Therefore, Freddie Mac's administrative 
expense rate has a smaller effect on required capital in both interest 
rate scenarios.
5. External Economic Conditions
a. House Prices
    Stress test results are also greatly affected by changes in 
external economic conditions. Seasoned mortgages in the base case 
simulations for June 1997 benefited from modest, but steady average 
house price appreciation of about three percent per year during the 
time between origination and the beginning of the stress period. In 
Simulations 46 and 47, shown in Table 22, the house price index was 
reduced by one percent and five percent, respectively, in the quarter 
immediately preceding the stress period (1997 Q2). That is, house price 
appreciation rates between the first and second quarters of 1997 were 
assumed to be one percentage point or five percentage points (4 or 20 
percentage points at an annual rate) less than they actually were. 
Subsequent house price appreciation rates are the same as in previous 
simulations.
[GRAPHIC] [TIFF OMITTED] TP13AP99.207

    When house prices are decreased by one percent, credit losses for 
each Enterprise increase by four to five percent in the up-rate 
scenario and by about seven percent in the down-rate scenario. The 
increases in credit losses when house prices are decreased by five 
percent are about five times as large as they are for a one percent 
house price decrease. The increases in incremental capital in both 
simulations are larger in the down-rate scenario because the decrease 
in house prices slows prepayment rates in that scenario, owing to 
higher probabilities of negative equity. Slower prepayment rates 
increase the volume of mortgages exposed to the risk of default. While 
loans also prepay more slowly in the up-rate scenario, prepayment rates 
in the base case simulation for that scenario are already so slow that 
a similar percentage change has little absolute effect.
    The slowing of prepayment rates with lower house prices in the 
down-rate scenario also produces two benefits that offset much of the 
increase in loan losses: guarantee fee income and net interest income 
increase. The key factor causing the effects on required capital to be 
larger in the down-rate scenario is that discount rates are lower in 
that scenario, so the present value of similar additional credit losses 
is greater.
    Differences in the changes in required capital between the 
Enterprises primarily reflect lower additional credit losses for 
Freddie Mac. Fannie Mae's losses are higher because its owned or 
guaranteed loan volume was about 45 percent larger than Freddie Mac's 
in June 1997 and its credit losses per dollar of loans are 11 to 14 
percent higher in the simulations, owing to a somewhat riskier mix of 
loans.
b. Market Interest Rates
    The behavior of interest rates in the months before the starting 
date of the stress test can also have a significant effect on required 
capital. In the simulations shown in Table 23, all market yields were 
assumed to be 200 basis points higher (Simulation 46), or lower 
(Simulation 47) in the month preceding the stress test period (June 
1997) than they actually were.\48\ The principal means by which this 
change in market yields affects required capital is through the change 
it causes in market interest rates during the last nine years of the 
stress test.\49\
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    \48\ No changes were made to interest rates on asset, liability, 
or off-balance sheet positions that had been put in place during the 
month, but they constitute a small share of total positions, and the 
effects of adjusting interest rates for those positions would have 
been largely offsetting. Nor were any changes made to Enterprise 
hedge positions that they might have made had market yields actually 
changed.
    \49\ In the circumstances of June 1997 (or any other time since 
September 1991), the applicable statutory rule for determining the 
change in the ten-year constant maturity Treasury yield during the 
stress period is that it increases by 75 percent or decreases by 50 
percent from the average over the preceding nine months. If interest 
rates were 200 basis points higher in June 1997, stress test rates 
would have risen to a level 200  9  x  1.75 = 39 basis 
points higher for the last nine years in the up-rate scenario. And, 
in the down-rate scenario, rates would have decreased to a level 200 
 9  x  0.50 = 11 basis points higher. Similarly, if interest 
rates were 200 basis points lower in June 1997, stress test rates 
would have been 39 basis points lower in the last nine years of the 
up-rate scenario and would have fallen to a level 11 basis points 
lower in the last nine years of the down-rate scenario. These 
differences are incorporated in Simulations 46 and 47.

[[Page 18112]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.208


    In Simulation 46, the hypothetical increases in June 1997 yields 
make the stress test more severe in the up-rate scenario and less 
severe in the down-rate scenario. Simulation 47 does the reverse. The 
size of the effects is much greater for Fannie Mae because its asset 
size was roughly double Freddie Mac's at the time, and because Fannie 
Mae's interest rate risk was less fully hedged then Freddie Mac's. 
Although changes in net interest income accounted for nearly all of the 
change in required capital, differences in prepayment rates in the 
down-rate scenarios of both simulations affected required capital 
through changes in other income and expense categories. Lower 
prepayment rates in Simulation 46 increased credit losses, but also 
increased guarantee fees. Higher prepayment rates in Simulation 47 
decreased credit losses and guarantee fees.
c. Sensitivity to Risk Characteristics in Different Economic 
Environments
    The results of the sensitivity analysis discussed above are 
dependent on the risk structure of the Enterprises and the economic 
conditions of June 1997. For example, as discussed above, credit losses 
on seasoned loans vary depending on house price behavior between the 
time of origination and the start of the stress test. At higher 
interest rate levels, the consequences of imperfectly matched assets 
and liabilities would be greater because stress test changes in 
interest rates would be larger. At lower interest rate levels, the 
effects would be smaller. Different Enterprise hedging strategies could 
affect reported sensitivities because they could result in a different 
pattern of profits and losses during the stress period, which could 
affect the role of taxes. Changes in common stock dividend payouts 
could affect the impact of dividends during the first year of the 
simulations.

C. Implications of the Proposed Rule

    The Enterprises perform an important role in the nation's housing 
finance system. Although the current risk of an Enterprise failure is 
small, the continued financial health of the Enterprises cannot be 
taken for granted. Over the past two decades, failures of financial 
institutions have been commonplace, including more than 2900 banks and 
thrifts and a number of securities firms. The risks associated with 
Fannie Mae and Freddie Mac differ in some important ways from those 
associated with banks, thrifts, and securities firms. However, 
government sponsored enterprises are not immune to failure. Fannie Mae 
encountered serious financial difficulty in the early 1980s, recovering 
in large part because of a fortuitous decline in interest rates, and 
the Farm Credit System experienced serious problems later in the 
decade. Because of the Enterprises' key role and important public 
mission, Congress created OFHEO to ensure their safe and sound 
operation. The current combined obligations of the Enterprises amount 
to more than $1.7 trillion, and unlike banks, thrifts, and securities 
firms, no Enterprise obligations are backed by an insurance fund that 
could contribute toward meeting creditor claims.
    The risk-based capital rule (in conjunction with OFHEO's other 
regulatory tools) is intended to reduce the risk of financial failure 
of an Enterprise. The rule can contribute to that goal by requiring the 
Enterprises to hold more capital or take less risk than they otherwise 
would in some or most potential circumstances, particularly those 
circumstances in which the danger of failure is greatest. In 
circumstances in which some capital or risk adjustment is necessary, 
the rule gives an Enterprise the flexibility to choose whether more 
capital, less risk, or a combination of the two best suits its business 
needs.
    OFHEO believes that the proposed rule would effectively serve its 
intended role. By promoting the Enterprises' safety and soundness, the 
regulation promotes their ability to continue to carry out their public 
purposes.\50\ These include providing stability in the secondary market 
for residential mortgages and providing access to mortgage credit in 
central cities, rural areas, and underserved areas.
---------------------------------------------------------------------------

    \50\ 1992 Act, section 1302(2) (12 U.S.C. 4501(2)).
---------------------------------------------------------------------------

    Capital reduces the risk and costs of failure by absorbing losses. 
For most firms, debt markets provide strong capital discipline, 
penalizing a firm that is excessively leveraged with higher borrowing 
costs. That discipline is largely lacking for the Enterprises because 
of their government sponsored enterprise status. The lack of normal 
market discipline makes capital requirements particularly important for 
the Enterprises.
    The minimum capital regulation, currently in place for the 
Enterprises, provides important protection against failure. It requires 
the Enterprises to have a minimally acceptable level of capital in 
relation to their overall size, regardless of their measurable risk. 
The establishment of the minimum capital standard was accompanied by 
considerable increases in capital at both Enterprises. Because, 
however, it is based on simple leverage ratios, it will not be 
sufficient if an Enterprise chooses to take risky financial positions 
or if market conditions move adversely and increase the risk of what 
had been less risky positions. By contrast, the proposed rule is quite 
sensitive to risk. It would require an Enterprise to increase capital 
when risk rises, well before the potential adverse

[[Page 18113]]

consequences of the rise would be reflected in the Enterprise's 
financial statements. Each of the two capital rules is an essential 
complement to the other.
1. Capital Requirements Under the Proposed Rule
    Consistent with the purpose of reducing the risk of Enterprise 
failure, the proposed rule can be expected to influence how the 
Enterprises manage their risk and the amount of capital they hold. 
Table 24 shows actual total capital (amounts available to meet the 
risk-based capital requirement) and required total capital under the 
proposed rule for two dates: September 30, 1996 and June 30, 1997.\51\ 
It also shows actual core capital (amounts available to meet the 
minimum capital requirement) and required core capital on the same 
dates. The difference between total capital and core capital is that 
total capital includes general loss reserves, while core capital does 
not.
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    \51\ These results include estimated effects on required total 
capital for three provisions of the proposed rule that require 
credit ratings: credit losses on non-mortgage investments; on 
derivative contracts; and on rated mortgage-related securities, such 
as mortgage revenue bonds. OFHEO assumed that 50 percent of non-
mortgage investments are rated AAA, 35 percent are rated AA, and 15 
percent are rated A. The percentages for derivative contracts are 
85, 15, and 0, respectively; and those for rated mortgage-related 
securities are 70, 30, and 0, respectively. The results do not 
reflect the effects of master netting agreements, nor haircuts on 
foreign-denominated contracts. Multifamily credit enhancements, 
other than those for Fannie Mae's DUS product are not modeled 
explicitly, but are assumed to reduce loss severities by 15.9 
percentage points.
[GRAPHIC] [TIFF OMITTED] TP13AP99.209

    Table 25 shows the surplus or deficit of total capital for both 
interest rate scenarios. The risk-based capital requirement for an 
Enterprise is based on the scenario that would result in the greatest 
deficit or smallest surplus. To meet the requirement, an Enterprise 
must not have a capital deficit in either scenario. Freddie Mac would 
have had a risk-based capital surplus of 28 percent on the 1996 date 
and 19 percent in 1997, while Fannie Mae would have had a deficit on 
each date of 21 percent. In contrast, both firms met the existing 
minimum capital standard on both dates, with surpluses ranging from 4 
percent to 11 percent. Thus, the risk-based capital requirement would 
have been much higher than the minimum capital requirement for Fannie 
Mae, even after taking account of the differences in the definition of 
capital under the two standards. For Freddie Mac, however, the minimum 
capital requirement would have been higher than the risk-based capital 
requirement. Thus, the risk-based standard would not have imposed any 
additional requirement on Freddie Mac on those dates. The primary 
reason Fannie Mae's risk-based capital requirement would have exceeded 
its minimum capital requirement, while Freddie Mac's would not, is that 
Freddie Mac's asset/liability structure was more fully hedged against 
interest rate risk than Fannie Mae's.

[[Page 18114]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.210


    Risk-based capital requirements in the future may vary 
significantly, depending not only on the Enterprises' assets and 
obligations, but also on contemporary economic conditions. Declines in 
house prices in the years preceding the starting date of the stress 
test can greatly raise capital requirements under the proposed rule, 
and rapid house price appreciation during these years can greatly 
reduce them. Unhedged interest rate exposures would require greater 
capital when interest rates are higher at the start of the stress 
period because changes in interest rates during the stress period will 
be greater. The reverse is true when interest rates are lower. Economic 
environments entailing greater than usual uncertainty about future 
interest rates or mortgage defaults will be accompanied by higher costs 
for hedges, such as callable debt or credit enhancements. In the 
absence of a risk-based capital standard, an Enterprise might choose to 
maintain capital and hedges that would be sufficient to meet the 
proposed standard in low risk environments, but might not do so in high 
risk environments owing to the higher cost of capital and hedges in 
such environments.
2. Enterprise Adjustments To Meet the Proposed Standard
    An Enterprise with capital and risk preferences that are not 
consistent with the proposed standard could adjust to the standard by 
either increasing capital or decreasing risk or both. Capital can be 
increased by reducing share repurchases, adjusting dividends, or 
issuing new equity shares. Enterprise risk can be reduced by increasing 
the use of interest rate and credit risk hedges, after risk is taken 
on, or by reducing the amount of risk taken on.
    Financial markets currently provide a wide range of hedges against 
interest rate risk. These include, among others: callable long-term 
debt, caps and floors, and swaps and swaptions. Adding interest rate 
risk hedges may frequently be cheaper than increasing equity. For 
example, based on the differences in results of Simulations 40, 41, and 
42 shown in Table 20, Fannie Mae could have met the proposed standard 
in June 1997 by issuing $22 billion of callable ten-year notes and 
using the proceeds to pay off $14 billion of short-term debt and 
repurchase $8 billion of ten-year notes.\52\ Given the market yields at 
that time, such a change in debt structure would have cost less than 
$200 million on an annual basis, after taxes. However, because this 
debt restructuring would have provided substantial benefits in terms of 
reduced risk, the net cost would have been much lower.
---------------------------------------------------------------------------

    \52\ The interest rates of long-term debt used in the 
simulations roughly reflect what the average cost of such 
instruments would have been in June 1997.
---------------------------------------------------------------------------

    Changes in an Enterprise's asset/liability structure to reduce 
interest rate risk, such as the one described in the above example, may 
be much cheaper than raising new equity. If the annual cost of equity 
capital is assumed to be 15 percent, the net cost of raising sufficient 
equity would have been roughly $385 million.\53\ Other forms of 
liability restructuring, or changes in the interest rate risk 
characteristics of the assets, might have resulted in lower costs than 
those estimated here for hypothetical changes in debt structure. Fannie 
Mae anticipated the likelihood of such opportunities in its comment on 
OFHEO's ANPR: ``* * * if the [mortgage] portfolio is in a position 
where its risk-based capital requirement exceeds its actual capital, 
the practical remedy would be to change the portfolio's asset/liability 
structure so that this is no longer the case.'' An alternative way for 
an Enterprise to reduce its interest rate risk is simply to reduce the 
size of its asset portfolio. Given the high profitability of those 
portfolios in recent years, that currently would not be a likely 
choice.
---------------------------------------------------------------------------

    \53\ In its analysis supporting its affordable housing goal 
rule, HUD used an estimate for the cost of equity capital of 17 
percent, but subsequent increases in price-earnings ratios suggest a 
smaller number for more recent dates. The cost calculation assumes 
that the additional equity would have replaced an equal amount of 
debt.
---------------------------------------------------------------------------

    Increasingly, credit risk can also be hedged in financial markets. 
Freddie Mac's 1998 MODERNS transaction effectively transferred a 
portion of the credit risk on its 1996 mortgage purchases to investors 
in the new securities.\54\ Further development of the credit 
derivatives market may provide additional opportunities for 
transferring credit risk in the future. An Enterprise can also reduce 
its credit risk by requiring or acquiring more credit enhancements. As 
an example, the Enterprises increased requirements for mortgage 
insurance on 95 percent LTV loans starting in 1995.
---------------------------------------------------------------------------

    \54\ Investor returns on the securities are dependent on the 
rate of defaults in a pool of mortgages representing 17.4 percent of 
Freddie Mac's single family, 30-year FRMs purchased in 1996.
---------------------------------------------------------------------------

    Finally, an Enterprise could adjust to a capital shortage by 
curtailing the size of its mortgage guarantee business. Such a measure 
is likely to be taken only as a last resort, as that business is the 
primary means by which an Enterprise fulfills its fundamental public 
purposes. As long as that business is profitable, an Enterprise is 
likely to prefer to restructure its asset/liability positions, obtain 
more credit risk hedges, or, if necessary, raise additional capital. If 
the Enterprise is financially safe and sound, raising additional equity 
capital should not be difficult. Because the proposed rule should help 
ensure the Enterprise's continued healthy financial condition, the rule 
would make it less, rather than more, likely that the Enterprise will 
need to restrict its activities.
3. Guarantee Fees
    It is unlikely that the proposed rule will have any material 
effects on the general level of guarantee fees charged by the 
Enterprises. The stress test results make it particularly unlikely that 
the rule would have any effects on guarantee fees in economic 
environments like those of the recent

[[Page 18115]]

past. Freddie Mac would have met the risk-based standard in 1996 and 
1997 by substantial margins, without any changes to its balance sheet 
or business operations. Thus, the risk-based capital standard would not 
have given Freddie Mac any cause to raise guarantee fee levels. Fannie 
Mae would not have been able to, if it wished to maintain its 
competitive position. In the future, there may be circumstances in 
which the capital or risk positions of both Enterprises are affected 
simultaneously by the risk-based standard. The analysis of such cases 
is more complicated. However, the duopolistic structure of the 
secondary mortgage market and the generally small impact of the 
guarantee business on required capital make it unlikely that the 
standard would affect guarantee fees in those circumstances, either.
    Guarantee fees compensate the Enterprises for assuming credit risk 
on the mortgages they purchase in the secondary market. They may be 
explicit, as they are for securitized loans, or implicit, as they are 
for loans purchased for Enterprise portfolios. These fees primarily 
cover expected credit losses and operating expenses, but include a 
return to the capital needed to protect against more severe credit 
losses in adverse environments. The need to provide such a return 
effectively makes capital a component of cost in the Enterprises' 
secondary market activities.
    In a fully competitive market, a regulation (such as a capital 
regulation) that raises the marginal costs of all firms in that market 
would result in higher prices (guarantee fees in this case). However, 
the secondary mortgage market is not fully competitive.\55\ Fannie Mae 
and Freddie Mac constitute virtually the entire buy side of the 
secondary market for fixed-rate conforming, conventional mortgages, 
making that market a duopoly.\56\ In a duopoly, the two firms generally 
exercise market power by charging prices (the guarantee fee) in excess 
of marginal cost, and thereby recognizing economic profits.
---------------------------------------------------------------------------

    \55\ For a fuller discussion of secondary mortgage market 
structure and behavior, see Benjamin E. Hermalin and Dwight M. 
Jaffe, ``The Privatization of Fannie Mae and Freddie Mac: 
Implications for Mortgage Industry Structure,'' in Studies on 
Privatizing Fannie Mae and Freddie Mac, U.S. Department of Housing 
and Urban Development, May 1996. This paper was jointly commissioned 
by HUD, the Department of the Treasury, the General Accounting 
Office, and the Congressional Budget Office.
    \56\ The ``buy side'' terminology here is traditional but 
confusing. The Enterprises are either buying mortgages or selling 
guarantees. Either way, they are charging implicit or explicit fees 
for assuming credit risk.
---------------------------------------------------------------------------

    In theory, the guarantee fee charged by Fannie Mae and Freddie Mac 
may range between the perfectly competitive rate (where the fee equals 
the firms' marginal cost) and the monopoly rate (where the fee 
maximizes the two firms' joint profits as if they were operating as a 
cartel). If the fee at which other firms may enter the market is less 
than the monopoly fee, then the maximum fee would be that at which 
entry would take place.
    The Enterprises' current guarantee fees reflect the profit-
maximizing decisions of both Enterprises. These decisions are affected 
by the degree of competition between the two firms, the threat of entry 
by other firms, and activities necessary to maintain or enhance the 
value of their public charters. The current level of guarantee fees 
already reflects the maximum guarantee fees that each Enterprise feels 
it can charge without reducing long-run profits. If this were not the 
case, Enterprise shareholders likely would object. In such 
circumstances, a small increase in capital (or any other) cost is 
unlikely to affect guarantee fees. Only if the cost increase was 
sufficiently large to raise marginal cost (including an adequate return 
to attract capital) above the current fee level, would a fee increase 
reasonably be expected.
    The Treasury Department and the Congressional Budget Office 
estimated in 1996 that the Enterprises collected roughly five basis 
points (0.05 percent) in fees for their mortgage-backed security 
guarantees above what they would need to recover costs plus a normal 
profit margin.\57\ After taxes (at an effective rate of 30 percent), 
that amounts to 3.5 basis points. A risk-based capital standard that 
raised the capital costs associated with the Enterprises' guarantee 
business by less than that amount would still allow the Enterprises to 
earn returns above a normal profit margin.
---------------------------------------------------------------------------

    \57\ U.S. Department of the Treasury, The Government Sponsorship 
of the Federal National Mortgage Association and the Federal Home 
Loan Mortgage Corporation, July 11, 1996; The Congressional Budget 
Office, Assessing the Public Costs and Benefits of Fannie Mae and 
Freddie Mac, May, 1996.
---------------------------------------------------------------------------

    If a new capital standard required an Enterprise to increase its 
equity when it increased its guarantee business, its capital cost per 
dollar of new guarantee business would be the amount of additional 
capital required times the cost of new equity capital, perhaps 15 
percent. The proposed rule, however, provides an alternative to raising 
equity, which is to reduce some other risk. As shown in the previous 
section, Fannie Mae could meet an overall higher capital requirement of 
$3.68 billion at an after-tax cost of less than $200 million in June 
1997. The cost per dollar of additional capital requirements was only 
about 5.4 cents (0.20  3.68). An additional dollar of capital 
requirements associated with new guarantee business could be met in the 
same way. Based on that cost of capital, if an additional dollar of 
guarantee business caused required capital under the new standard to be 
65 basis points greater than under the existing standard, the 
additional capital cost would be only as great as the duopoly surplus 
margin of 3.5 basis points (65  x  .054 = 3.5).
    In the absence of a risk-based capital standard, regulatory capital 
costs are based on the existing minimum capital leverage ratio for 
mortgage-backed security guarantees, which is 0.45 percent (45 basis 
points). A comparison with the incremental capital required for sold 
loans under the risk-based capital requirement must take into account 
that the leverage requirement can be met only with equity (core) 
capital, while the risk-based requirement can be met with both equity 
and reserves (total capital). Reserves for losses on mortgage-backed 
security guarantees average about seven basis points per dollar of 
guarantees at both Enterprises, so the comparable minimum capital 
requirement in terms of total capital is 52 basis points. Thus, a risk-
based capital standard could potentially raise the incremental amount 
of total capital required for sold loans to as much as 117 basis points 
(52 + 65) and still allow the Enterprises to earn sufficient profits to 
continue to attract capital.
    Even greater increases would be unlikely to affect guarantee fees 
in circumstances when the capital and risk decisions of one or both 
Enterprises are unaffected by the risk-based standard, as was 
presumably the case for Freddie Mac on the two recent dates for which 
risk-based capital calculations have been performed. If the risk-based 
standard were binding (affected capital or risk decisions) for only one 
of the Enterprises, then, even if its incremental risk-based 
requirements for sold loans were very much higher than the minimum 
capital ratio, it would be difficult for that Enterprise to raise 
guarantee fees independently. Doing so likely would cause it to lose 
market share and profits to the other Enterprise.
    Even if the risk-based standard were binding on both Enterprises, 
it appears unlikely that the proposed standard would raise the capital 
required for the Enterprises' mortgage guarantee business to as much as 
117 basis points. The results of a simulated increase in

[[Page 18116]]

overall MBS guarantee volumes, shown in Table 6, indicate that the 
incremental capital required in 1997 for the up-rate scenario of the 
risk-based standard was well below the 52 basis points needed to meet 
the minimum capital standard. In the down-rate scenario, incremental 
capital of as much as 89 basis points would have been needed, but that 
is still substantially below the 117 basis points level that 
potentially would trigger a rise in guarantee fees.
    While the results referred to in Table 5 are informative, an 
Enterprise evaluating the capital costs associated with its mortgage 
guarantee business would properly focus on its prospective costs at 
future dates. To do so, it would want to estimate the likelihood of its 
being bound by the risk-based standard in the future, and if it thought 
it would be bound, the relative likelihood of being bound by the up-
rate and down-rate scenarios. It would also want to make informed 
guesses about the other Enterprise's estimations on its own behalf. 
Finally, it would want to estimate the likelihood of significantly 
higher incremental capital requirements for sold loans under the risk-
based standard.
    These incremental requirements will be affected by the pace of 
house price appreciation in the years preceding the date of capital 
calculation. The figures in Table 5 reflect annual appreciation of 
about three percent, lower than long-run historical averages. If an 
Enterprise anticipated stagnant or declining house prices over an 
extended period of time, and if it believed both itself and the other 
Enterprise likely would be bound by the risk-based standard, 
particularly the down-rate scenario, it might have an incentive to 
raise guarantee fees. In such a circumstance, its expected losses would 
also rise, and likely by far more than its capital costs. The higher 
expected losses would, in that case, be the principal cause of higher 
fees.
    A riskier interest rate environment could also affect projected 
capital costs. If the cost of interest rate risk hedges rose 
dramatically, so that it became cheaper to meet shortfalls in required 
capital by raising new equity than by increasing interest rate hedges, 
any increase in capital required by an Enterprise's sold loans would be 
more costly and more likely to lead to a small increase in guarantee 
fees. However, providing adequate protection in unusually risky 
economic environments, such as those with much higher interest rate 
hedging costs or persistent weakness of house prices is a fundamental 
purpose of the risk-based capital standard.
    OFHEO has also considered the possibility that the proposed 
standard, while not affecting the general level of guarantee fees, 
could affect the fees charged directly or indirectly on loans made to 
low income borrowers. Such effects are unlikely and would, in any 
event, be minimal. Consequently, the risk-based capital standard will 
not significantly affect the Enterprises' ability to purchase 
affordable housing loans. These conclusions are based on several 
considerations. First, the capital surpluses that Freddie Mac would 
have held in 1996 and 1997 under the rule show that no changes in any 
Enterprise fees or loan-purchase practices would have been justified in 
recent economic environments.
    Second, with respect to potentially more adverse environments, the 
capital cost of single family loans meeting the Enterprises' affordable 
housing goals should not be materially different, on average, from the 
cost of other loans. The stress test makes no specific distinctions 
among loans to different income groups. However, the stress test does 
distinguish single family loans according to LTV class and some 
Enterprise affordable products are high LTV loans. The simulation 
results in Section II. B., Sensitivity of Capital Requirements to Risk, 
show that high LTV single family loans are generally riskier and affect 
risk-based capital requirements more than other loans. However, the 
overall LTV distribution of single family loans purchased by Fannie Mae 
and Freddie Mac for low-and moderate-income borrowers (borrowers with 
less than area median income) is practically the same as the LTV 
distribution of all their purchased loans. In fact, only a small 
percentage of the loans to low- and moderate-income borrowers purchased 
by the Enterprises are high LTV loans (those with LTV ratios above 90 
percent).
    Third, while high LTV loans have much higher than average risk, the 
simulation results overstate the capital implications of those loans. 
The results of Simulations 13 and 15, in Table 12, show incremental 
capital required under the risk-based standard for new and four-year-
old loans, as of June 1997. For a weighted average of Enterprise loans 
guaranteed at that time, these incremental requirements were about 170 
basis points above the comparable minimum capital ratio in the up-rate 
scenario, and about 325 basis points above in the down-rate scenario. 
Those differences in capital required, however, overstate the impact of 
high LTV loans because they assume only an average level of guarantee 
fees. As discussed earlier, the Enterprises generally charge higher 
fees implicitly on such loans by adjusting the average fees charged to 
lenders according to the average risk of the loans they deliver. And as 
shown by the comparison of Simulations 2 and 3, in Table 8, differences 
in guarantee fees affect incremental capital requirements. The 
overstatement may be increased by the assumption that the Enterprises 
have priced these loans based on the incremental capital needed to meet 
the minimum standard. Both Enterprises use internal capital models that 
reflect the higher risk of high LTV loans and already may incorporate 
higher capital costs into the implicit fees charged for these loans.
    Fourth, the capital implications of multifamily loans, which 
predominately benefit low- and moderate-income households, are mixed 
and serve, in some circumstances, as hedges for other high-risk loans. 
Simulations 22 to 25 show a wide variety of incremental capital 
requirements under the risk-based standard for June 1997. On a weighted 
average basis, accepting credit risk on multifamily loans lowered risk-
based requirements in the down-rate scenario and raised them somewhat 
more than minimum capital requirements in the up-rate scenario. The 
results in the down-rate scenario are the reverse of the pattern for 
high LTV single family loans, so that higher costs on high LTV single 
family loans are substantially offset by lower costs on multifamily 
loans. In the up-rate scenario, the potential effects of high LTV loans 
and multifamily loans are similar, but not large.
    Finally, even if the proposed rule did require some additional 
capital against a portion of the Enterprises affordable housing 
activities, such a requirement would be consistent with the 
Enterprises' charters and public mission. The Enterprises' charters 
specifically state that the return on required lending to low-and 
moderate-income borrowers may be less than the return earned on other 
activities.
4. Mortgage Interest Rates
    The primary effects of the Enterprises' activities on mortgage 
interest rates occur through their roles as mortgage security 
guarantors. Mortgage security yields are determined in capital markets, 
and the interest rates borrowers pay reflect those yields plus the 
margins retained by the Enterprises, as guarantee fees, and those 
retained by lenders and servicers. Because of the dominant role of the 
Enterprises in the market for conforming, single family mortgages, 
increases in their guarantee fees would raise lenders' costs and 
translate fairly directly to changes in borrowers' costs.

[[Page 18117]]

However, because the proposed rule likely will have no material effect 
on guarantee fees, it would not have a significant effect on mortgage 
rates through the Enterprises' roles as mortgage guarantors.
    As investors in mortgages and mortgage securities, the Enterprises 
may also affect mortgage rates indirectly. They now hold roughly an 
eighth of all conforming, single family mortgages, and massive changes 
in their purchase volumes could have some effect, at least temporarily, 
on prices in that market. However, the Enterprises do not dominate the 
mortgage investment asset market in the same way that they dominate the 
market for guarantees on conforming loans. Consequently, the effects on 
mortgage security yields of even substantial changes in their 
investment in mortgage securities would be small. Furthermore, the 
proposed rule is unlikely to have a substantial effect on Enterprises' 
purchases of mortgage assets. Freddie Mac added roughly $100 billion to 
its portfolio in the four years preceding the June 1997 simulations and 
still easily met the requirements of the proposed rule. Thus, it is 
unlikely that the proposed rule would affect the mortgage interest 
rates paid by borrowers through the Enterprises' roles as mortgage 
investors, either.

III. Issues, Alternatives Considered

A. Mortgage Performance

    The 1992 Act requires the risk-based capital test to subject the 
Enterprises to specified adverse credit and interest rate risk 
conditions to determine the level of capital needed to survive a 
hypothetical ten-year stress period. The 1992 Act does not specifically 
refer to mortgage performance, but rather discusses the credit-risk 
portion of the stress test as including rates of mortgage default and 
loss severity. As a convenience, OFHEO used the term ``mortgage 
performance'' in the ANPR to facilitate discussion of the essential 
elements of credit risk, mortgage default and loss severity, as well as 
mortgage prepayment, a key element of interest rate risk. The 1992 
Act's requirement to determine a prepayment experience consistent with 
the stress period is also relevant to credit risk, because loans that 
are paid off prior to maturity affect default rates by reducing the 
number of loans that have the potential to default and by increasing 
the proportion of loans likely to default. Together, default, 
prepayment, and loss severity define how a portfolio of mortgages will 
perform in the proposed stress test. That performance is a key element 
in determining the ability of an Enterprise to withstand the economic 
shocks imposed by the stress test.
    To determine the level of capital needed to survive the stress 
test, the proposed regulation uses a monthly cash flow model to project 
the performance of each Enterprise during the stress period. Underlying 
the simulation of mortgage and mortgage security cash flows are models 
that project mortgage performance during the stress period.
    This section discusses the issues, alternative approaches and 
related ANPR comments that were considered by OFHEO in developing 
models to project mortgage performance under economic conditions 
specified in the l992 Act. Section III. A. 1., Statutory Requirements 
describes relevant statutory requirements. Section III. A. 2., Overview 
of Mortgage Performance, explains how mortgage performance is measured 
and projected in the stress test. Next, in section III. A. 3., 
Statistical Models of Mortgage Performance, through section III. A. 7., 
Relating Losses to the Benchmark Loss Experience, the issues 
encountered by OFHEO in developing models of mortgage performance, 
along with relevant comments received in response to the ANPR, are 
discussed. Section III. A. 3., Statistical Models of Mortgage 
Performance, discusses OFHEO's decision to employ statistical models to 
predict default, prepayment, and severity rates. Section III. A. 4., 
General Methodological Issues, reviews general methodological issues 
encountered in making product distinctions and developing loan and 
property value data for use in estimating the statistical models and in 
applying those models in the stress test. Section III. A. 5., Default/
Prepayment Issues, details the construction of the default and 
prepayment models, including use of conditional rates of default and 
prepayment, use of joint models of default and prepayment, and choice 
of the explanatory variables used in the models. Section III. A. 6., 
Loss Severity, moves from default and prepayment to issues encountered 
in modeling loss severity rates. Section III. A. 7., Relating Losses to 
the Benchmark Loss Experience, discusses issues arising from the 
statutory direction to reasonably relate stress test losses to the 
benchmark loss experience.
1. Statutory Requirements
    The 1992 Act mandates a stress test based on a regional recession 
involving the highest rates of default and loss severity experienced 
during a period of at least two years in an area containing at least 
five percent of the total U.S. population.\58\ This mandate required 
identifying a benchmark loss experience, which is the default and 
severity behavior of mortgage loans, in a place and time meeting 
statutory requirements, that resulted in the highest loss rate for any 
such place and time.\59\ In this context, default and severity behavior 
means the frequency, timing, and magnitude of losses on mortgage loans, 
given the specific characteristics of those loans and the economic 
circumstances affecting those losses. The 1992 Act requires that 
default and severity rates in the stress test be reasonably related to 
this benchmark loss experience. In contrast, the 1992 Act does not 
prescribe any particular experience for the third key component of 
mortgage performance, prepayment. Rather, the Act requires that the 
Director determine prepayment levels, ``on the basis of available 
information, to be most consistent with the stress period.'' \60\
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    \58\ 1992 Act, section 1361(a)(1) (12 U.S.C. 4611(a)(1)).
    \59\ See 61 FR 29592, June 11, 1996, in which OFHEO proposed 
procedures for establishing the benchmark loss experience.
    \60\ 1992 Act, section 1361(b)(2) (12 U.S.C. 4611(b)(2)).
---------------------------------------------------------------------------

    The 1992 Act requires the Director to take into account appropriate 
distinctions among mortgage product types and differences in loan 
seasoning. It also authorizes the Director to also take into account 
any other factors that the Director deems appropriate.\61\ The statute 
defines the term ``seasoning'' as ``the change over time in the ratio 
of the unpaid principal balance of a mortgage to the value of the 
property by which such mortgage loan is secured.'' \62\ The importance 
of seasoning is that a decline in a property's value can result in 
negative equity, the factor most predictive of rates of default.
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    \61\ 1992 Act, section 1361(b)(1) (12 U.S.C. 4611(b)(1)).
    \62\ 1992 Act, section 1361(d)(1) (12 U.S.C. 4611(d)(1)).
---------------------------------------------------------------------------

    The 1992 Act defines mortgage product type as a classification of 
one or more mortgage products having similar characteristics with 
respect to the property securing the loan, the interest rate, the 
priority of the lien, the term of the mortgage, the owner of the 
property (owner-occupant vs. investor), the nature of the amortization 
schedule, and any other characteristics as the Director may determine. 
Specifically, the 1992 Act requires OFHEO to take into account 
distinctions between different mortgage types, such as: (1) properties 
consisting of 1-4 residential units and those containing more than four 
units;

[[Page 18118]]

(2) fixed and adjustable interest rates; (3) first and second liens; 
(4) terms of 1-15 years, terms of 16-30 years and terms of more than 30 
years; (5) owner occupants and investors; and (6) fully amortizing 
loans and loans that are not fully amortizing.
    The 1992 Act prescribes two interest rate scenarios, one with rates 
falling and the other with rates rising.\63\ In each scenario, the ten-
year constant maturity Treasury yield (CMT) experiences a significant 
change during the first year of the stress test, and then remains at 
the new level during the remaining nine years of the stress test. The 
capital requirement for each Enterprise is based on the scenario with 
the more adverse impact.\64\ The 1992 Act recognizes that interest 
rates are related to credit risk as well as interest rate risk, 
specifically requiring that credit losses be adjusted for a 
correspondingly higher rate of general price inflation if applying the 
stress test results in an increase of more than 50 percent in the ten-
year CMT.\65\
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    \63\ 1992 Act, section 1361(a)(2) (12 U.S.C. 4611(a)(2)).
    \64\ 1992 Act, section 1361(a)(2) (12 U.S.C. 4611(a)(2)).
    \65\ 1992 Act, section 1361(a)(2)(E) (12 U.S.C. 4611(a)(2)(E)).
---------------------------------------------------------------------------

2. Overview of Mortgage Performance
    The amount of capital needed to survive the stress conditions 
prescribed by statute is determined by the overall financial 
performance of the Enterprises' starting books of business, including 
all assets, liabilities, and off-balance sheet obligations, under the 
stress conditions. Mortgage performance contributes to the overall 
financial performance of an Enterprise during the stress period, 
because various sources of income and expense reflected on an 
Enterprise's income statement depend directly on mortgage performance. 
For example, guarantee fee income on securitized loans, net interest 
income on retained loans and securities, and losses on defaulting loans 
(offset by the receipt of private mortgage insurance payments and other 
third-party credit enhancements) all depend on the projected default 
and prepayment behavior of the underlying mortgage assets.
    For purposes of the proposed regulation, mortgage performance is a 
function of the survival or termination of loans and, ultimately, the 
associated cash flows. Loan terminations can occur either through 
default (borrower failure to pay) or through prepayment (early payment 
in full). Prepayments have a significant impact on credit risk, because 
they affect the timing and rates of default. Prepayments also affect 
Enterprise income, because they cut off the income stream from interest 
payments or guarantee fees. Defaults likewise cut off the income 
stream, and, in addition, result directly in credit losses.
    To understand how the stress test generates and uses mortgage 
performance information, the test may be viewed as comprised of three 
elements--models, stress test specifications, and data inputs. In the 
context of mortgage performance, the models are sets of equations 
designed to predict the performance of any group of Enterprise 
mortgages under any given set of economic circumstances. The model 
equations themselves are ``estimated'' based upon OFHEO's historical 
database of mortgage information to predict the most likely default and 
severity rates for any given group of mortgages under any given pattern 
of interest rates and house prices. These models are generic tools that 
could be used in many different stress tests with different 
specifications. The specifications actually define the ``stress'' in 
the stress test. They include adjustments to reflect statutory 
requirements, such as the requirement that default and severity rates 
be ``reasonably related'' to the benchmark experience or that interest 
rate increases greater than 50 percent reflect a correspondingly higher 
rate of inflation. The specifications also include the house price and 
residential rent paths and the interest rates that will apply during 
the stress period. The data inputs to the models can change each time 
the stress test is run. The data inputs include data on the 
characteristics of loans owned or guaranteed by the Enterprises, 
starting interest rates, and updated house and residential rent price 
indexes, which are used to calculate current equity in the loan 
collateral properties.
    The general approach of the stress test to mortgage performance 
involves three main steps: (1) estimation of statistical models of 
mortgage performance (default, prepayment, and loan loss severity) 
using Enterprise data covering a wide range of historical experience; 
(2) adjustments to the statistical models to assure a reasonable 
relationship to the benchmark loss experience; and (3) application of 
the adjusted models to starting Enterprise mortgage portfolios in the 
stress test. To assist the reader in understanding the more detailed 
discussion of mortgage performance issues that follows, this section 
provides a brief summary of some key issues concerning of the statutory 
requirement to ``reasonably'' relate the performance of mortgages in 
the stress test to the benchmark experience.
    Because the benchmark sample contained only newly-originated, 
fixed-rate, 30-year, owner-occupied, single family loans, the stress 
test could not simply apply the rates of default and losses in the 
benchmark loss experience and still take into account differences in 
mortgage product types, seasoning of mortgages, and other factors the 
Director considers appropriate, as required by the 1992 Act.\66\ Thus, 
the first issue considered by OFHEO was how to link mortgage 
performance in the stress test to the benchmark loss experience. The 
primary question was whether to use a model-based approach to help link 
the performance of an Enterprise's current loan portfolio to the 
benchmark loss experience, or to rely upon a less sophisticated, but 
less risk-sensitive approach. For reasons discussed under section III. 
A. 3., Statistical Models of Mortgage Performance, OFHEO concluded that 
the benefits of using a model-based approach exceed any potential 
shortcomings.
---------------------------------------------------------------------------

    \66\ 1992 Act, section 1361 (b)(1) (12 U.S.C. 4611 (b)(1)).
---------------------------------------------------------------------------

    The next key issue was the choice of variables to include in any 
statistical equations that would be part of a (statistical) model of 
mortgage performance. OFHEO's choices in this regard were again 
governed by the need to meet the multiple statutory objectives 
described above, while also implementing a credit stress test based on 
the historical benchmark loss experience. The stress test does not 
project all differences in loan performance that may have been 
identified in previous research. Rather, the factors used to project 
mortgage performance are limited to those necessary to: (1) reflect 
differences in characteristics of loans in implementing the credit risk 
stress component of the stress test as required by the 1992 Act; and 
(2) reflect differences in the interest rate environments experienced 
by the loans in the stress test.
    Other factors that relate to or explain differences in mortgage 
performance are not, in OFHEO's view, appropriate to the proposed 
regulation. Specifically, the stress test does not attempt to adjust 
losses by incorporating factors to reflect changes in Enterprise 
business practices subsequent to the benchmark loan origination and 
loss experience.\67\

[[Page 18119]]

OFHEO believes that such adjustments would undermine the purpose and 
intent of the statutory requirements to implement a credit stress test 
based on the benchmark loss experience. In addition, although some 
business practices that contributed to the losses of the past may have 
been improved over time, a new severe economic environment may expose 
other unobservable weaknesses. Furthermore, in reasonably relating 
starting position loan portfolios to the ``experience'' of the 
benchmark loans, it is not possible to separate the effects of business 
practice from other aspects of the benchmark economic environment.
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    \67\ For example, both Enterprises have made changes to their 
single family underwriting standards and practices since the time 
the benchmark loans were originated in 1983-84, but no underwriting 
variable is included. This particular issue is discussed in greater 
detail below, in the context of comments received in response to 
OFHEO's ANPR.
---------------------------------------------------------------------------

    The proposed regulation also does not incorporate economic or 
demographic variables that are not specifically prescribed for the 
stress test, such as unemployment or divorce rates. Nor are such 
variables included in the estimation of the statistical model used in 
the stress test. If they were to be included, it would be necessary to 
assume values for these factors in the stress period--values that are 
consistent with the benchmark experience. Such an approach would 
substantially increase the number of variables for which assumptions 
would be required during the stress period, without gaining significant 
value in predicting credit losses for Enterprise loan portfolios.
3. Statistical Models of Mortgage Performance
    A threshold issue for OFHEO was whether to develop statistical 
models of mortgage performance or to use a simpler approach, such as 
applying a table of historical default, prepayment, and loss severity 
rates.
a. ANPR Comments
    Most of the comments related to this issue suggested that the 
direct application of benchmark rates of default, prepayment and loss 
severity would be problematic. A number of respondents to the ANPR 
cautioned that direct application of benchmark default rates, which 
were experienced during a period of declining interest rates, would not 
be appropriate for the up-rate scenario of the stress test. Freddie Mac 
suggested that OFHEO adjust benchmark default rates to the interest 
rate environment or use a proportional downward adjustment to credit 
losses. Mortgage Risk Assessment Corporation (MRAC) stated that it is 
important to model the interaction between expected losses and expected 
prepayments. America's Community Bankers (ACB) recommended joint 
modeling of prepayments and defaults as the best way to capture 
adjustments to housing values.
    Fannie Mae, on the other hand, favored applying benchmark rates of 
default and loss severity directly. More specifically, Fannie Mae 
recommended that OFHEO model total loan terminations (defaults plus 
prepayments) using a commonly applied method of relating total 
terminations to interest rate movements (sometimes referred to as a 
``total terminations model''). Fannie Mae recommended that the default 
portion of total terminations should be based on observed default rates 
for mortgages from the benchmark experience, with appropriate 
distinctions based on different LTV ratios, mortgage product, and risk 
categories. The level of prepayments would be calculated by subtracting 
those defaults from total terminations. Fannie Mae stated that a 
statistical model designed to predict defaults and prepayments 
simultaneously would be difficult to replicate because it would employ 
computer simulation methods based upon random numbers, known as Monte 
Carlo simulations. Fannie Mae also expressed concern that the 
Enterprises would have difficulty managing capital requirements based 
on econometrically derived relationships, rather than on the certainty 
of defined historical loss rates.
b. OFHEO Response
    Based on its analysis of available information, including the ANPR 
comments and relevant academic literature, OFHEO found that statistical 
modeling has numerous advantages over alternative approaches, such as 
applying tables of default, prepayment, and loss severity rates from 
the benchmark experience.
    First, statistical models are able to provide valid outcomes when 
data inputs occur in different combinations from those observed in the 
available historical data. This capability is important, because the 
benchmark loss experience does not include large enough sample sizes 
for all relevant loan products and risk classes to allow direct 
application of benchmark loss rates to the Enterprises' starting loan 
portfolios. Statistical models based on large samples of loans can 
capture differential mortgage performance across a wide variety of 
products and still allow the performance of each product to be related 
to the benchmark experience. OFHEO has access to a rich database, 
consisting of millions of detailed loan records from the Enterprises, 
which allows for a statistical model of defaults and prepayments that 
can capture the nuances of product distinctions.
    Second, statistical models allow the stress test to extrapolate 
reasonably to out-of-sample events, such as the sustained adverse 
interest rate scenarios of the stress test.
    Third, applying statistical models of mortgage performance provides 
the ability to impose multiple statutory requirements in a logically 
consistent manner. For example, the 1992 Act specifies rates of default 
and losses in the stress test that are reasonably related to the 
benchmark loss experience. The 1992 Act also provides that the Director 
take into account the impact of ``mortgage seasoning'' and a variety of 
other factors that delineate various mortgage product types (property 
type, amortization type, amortization terms, ownership type, etc.). 
Statistical models allow the stress test to address all these statutory 
provisions when applying the two adverse stress test interest rate 
scenarios.
    OFHEO also found that using statistically derived models of 
default, prepayment, and loss severity together with a cash flow 
approach is the most accurate method to describe the financial 
performance of the Enterprises on a monthly basis over the ten-year 
stress period. Moreover, use of statistical models in the stress test 
is consistent with the 1992 Act \68\ and the Congressional expectation 
expressed in the House Report that the risk-based capital standard 
``will be an economic model that will test the enterprises' financial 
position under stressful economic situations.'' \69\ The House Report 
also noted that:
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    \68\ The 1992 Act directs OFHEO to include in the regulation 
``specific requirements, definitions, methods, variables, and 
parameters used under the risk-based capital test.'' This direction 
suggests that a statistical model was contemplated. The 1992 Act, 
section 1361(e)(2) (12 U.S.C. 4611(e)(2)). Further, the Director is 
required to ``provide copies of the statistical model or models'' to 
other government agencies. 1992 Act, section 1361(f) (12 U.S.C. 
4611(f)).
    \69\ H.R. Rep. No. 102-206, at 62 (1991). See also, S. Rep. No. 
102-282, at 24 (1992).

[t]he Department of the Treasury, the Congressional Budget Office, 
the General Accounting Office, the Office of Management and Budget 
and HUD have all stated that the proper way to ensure that Fannie 
Mae and Freddie Mac have adequate capital is to use traditional 
capital ratios in combination with sophisticated financial models, 
or risk-based capital stress tests.\70\
---------------------------------------------------------------------------

    \70\ H.R. Rep. No. 102-206, at 62 (1991).

    Fannie Mae's recommendation to estimate a statistical model of 
total terminations with default rates fixed at benchmark levels would 
make it more difficult for the stress test to satisfy the

[[Page 18120]]

provisions of the 1992 Act that require OFHEO to consider seasoning and 
the various loan characteristics described above. OFHEO is also 
concerned that a model that derives prepayment rates as suggested by 
Fannie Mae would not be consistent with section 1361(b)(2) of the 1992 
Act, which directs that ``[c]haracteristics of the stress period other 
than those specifically set forth in subsection (a), such as prepayment 
experience . . ., will be those determined by the Director, on the 
basis of available information, to be most consistent with the stress 
period.'' The consistency of prepayment experience with the stress 
period is best achieved by modeling both prepayment and default rates, 
rather than using a statistical model of terminations with embedded 
default rates that are not statistically determined.
    OFHEO also found that the total terminations models to which Fannie 
Mae refers are applied widely and usefully only in circumstances where 
credit losses are not an issue (for example, in pricing mortgage-backed 
securities for investors, where credit risk can be ignored because of 
agency guarantees), or when the available data do not allow the analyst 
to distinguish default terminations from voluntary prepayments (for 
example, in the pool level data available from commercial sources). 
This is not the case for the stress test.
    OFHEO is sensitive to Fannie Mae's concern that a statistical model 
of defaults and prepayments would be difficult to replicate. OFHEO does 
not propose to base any component of the stress test on random number 
(Monte Carlo) simulations. The model is straightforward and 
transparent, so that it will be possible for the Enterprises to project 
default and prepayment patterns in the stress period using their own 
information about the composition of their business, and recent 
economic trends.
    As for complexity, OFHEO believes that there is no fundamental 
difference in complexity between computing total termination rates from 
the models mentioned by Fannie Mae, and computing them from the 
separate default and prepayment rates generated by the model OFHEO has 
proposed. Once the statistical model OFHEO proposes has been estimated 
and calibrated, its application is no more difficult than the 
application of a table of historical default rates. That is, the model 
provides a means to ``look up'' the default or prepayment probabilities 
for loans with a particular set of characteristics. Further, under the 
approach proposed by Fannie Mae, the actual level of default rates 
applied in the stress period would not actually be fixed, but would 
vary with changes in the composition of an Enterprise's loan portfolio 
and trends in property values that update borrower equity values. Under 
either approach, determining the potential impact of market conditions 
or changes in an Enterprise's portfolio on its capital requirement is 
straightforward.
4. General Methodological Issues
    A number of general issues arose in the context of using 
statistical models to project mortgage performance in the stress test. 
These issues required decisions about how to account for product 
differences, what sources of historical data to use in estimating the 
statistical models, and what level of data aggregation to use to 
estimate and project mortgage performance. In addition, OFHEO received 
a number of comments in response to ANPR questions on property 
valuation issues. These were also considered in developing and applying 
statistical models of mortgage performance. Each of these areas is 
considered in the following sections.
a. Product Differences
    The 1992 Act requires the stress test to capture both the unique 
risk characteristics of various loan product and property types and 
adjust for changing economics (house prices and interest rates) over 
time. In deciding its approach to modeling default and prepayment 
rates, OFHEO found it necessary to treat single family and multifamily 
products separately because of the significant differences in 
collateral property types and loan terms explained below.
    The nature of the collateral property differs substantially between 
single family and multifamily loans. Nearly all single family property 
mortgages held by the Enterprises are owner-occupied.\71\ In contrast, 
multifamily collateral produces income from rentals. Multifamily 
mortgages are commercial loans on housing projects that compete for 
market share among a very mobile population with short-term rental 
contracts and relatively low moving costs. The household demographics 
of apartment renters vary greatly from those of single family 
homeowners and renters. The dynamics of construction cycles that 
accentuate market booms and busts are also different for single family 
and multifamily residences.
---------------------------------------------------------------------------

    \71\ Even those that are rentals rely upon the performance of 
one, or at most four, households.
---------------------------------------------------------------------------

    Single family and multifamily mortgages generally have different 
loan terms. In particular, to balance the desire of borrowers for 
flexibility with the needs of investors for stability, multifamily 
mortgages typically have ten- to fifteen-year balloon terms and initial 
yield-maintenance periods of seven to ten years. During the yield-
maintenance period, borrowers may prepay, but they are subject to a 
prepayment penalty until the maintenance period expires. Such 
prepayment disincentives are not used in single family lending. Also, 
in contrast to single family mortgages, multifamily mortgages tend to 
be non-recourse, which means that multifamily lenders and guarantors, 
have recourse only to the collateral, and not to the borrower's other 
assets and income.
    Because of these differences, OFHEO developed separate mortgage 
termination models for single family and multifamily mortgages, with 
all other property and product type differences handled as subsets of 
these two primary classifications. This approach is consistent with 
comments from HUD, Freddie Mac, ACB, and Mortgage Bankers Association 
of America (MBA). However, there are many issues common to both the 
multifamily and single family models, and the general modeling approach 
to both models is similar in many respects.
    In the ANPR, OFHEO solicited public comment on modeling approaches 
generally and, more specifically, on how to relate the credit risk of 
other loan product types to the 30-year fixed-rate mortgages used to 
identify the benchmark experience. These comments are addressed below 
in section III. A. 7., Relating Losses to the Benchmark Loss 
Experience.
b. Historical Analysis Data
    Another modeling issue faced by OFHEO was whether to use only 
Enterprise data to estimate statistical models, or to use data from a 
wider array of sources. A similar issue arose in the context of 
identifying the benchmark loss experience. After considering ANPR 
comments, OFHEO found that Enterprise data sets were the most relevant 
sources currently available for determining a benchmark loss 
experience, because Enterprise data is the most representative of the 
experience of loans owned or guaranteed by the Enterprises. Further, 
using Enterprise data is consistent with the general practice of 
banking and thrift industry regulators and credit rating agencies, 
which is to use data on the loss experience of comparable assets

[[Page 18121]]

for the relevant industry to determine credit quality and/or capital 
adequacy.
    For the same reasons, OFHEO also used Enterprise data to estimate 
the statistical models for default and prepayment in the proposed 
stress test. Using Enterprise data for this purpose provides 
consistency between the estimates of the benchmark loss experience, the 
estimation of the statistical models for default and prepayment, and 
the aggregation of loan level data to create starting position data for 
the stress test. It will also permit OFHEO to update the statistical 
models over time, as needed, to capture new performance dynamics and/or 
new products.
c. Aggregation
    Another threshold issue for OFHEO was how to aggregate loan level 
data to reduce the number of data records that must be stored and 
processed, while preserving sufficient detail to capture differences in 
loan performance among important risk classes in the stress test.
(i) ANPR Comments
    MRAC stated that a loan level model would be most appropriate if 
data were available, but a model that aggregates on the basis of the 
origination year, loan term, coupon rate and current loan-to-value 
ratio (CLTV) would be acceptable. Freddie Mac recommended that, if 
OFHEO were to use a joint default/prepayment model, OFHEO should 
construct a pool for each origination year, aggregated by mortgage 
product, property type, occupancy status, and CLTV. Both MRAC and 
Freddie Mac recommended that OFHEO not only aggregate data according to 
CLTV, but also use CLTV as an explanatory variable in statistical 
models of default and prepayment rates.
(ii) OFHEO Response
    OFHEO proposes to aggregate single family loan level data into loan 
groups based on the following characteristics: Enterprise, portfolio 
type (securitized vs. retained), product type, origination year, 
original LTV, original coupon, and region (Census division). 
Multifamily loans are aggregated using the same categorical variables 
as for single family loans, with an additional aggregation class for 
original debt-coverage-ratio values. Single family loans purchased 
during the stress period under existing contractual commitments are 
grouped using all of the characteristics of existing loans plus month 
of origination (representing the timing of delivery during the stress 
period). All loan group records include additional fields for measured 
characteristics, such as the total unpaid balance (UPB) for loans held 
in portfolio, UPB-weighted average values for guarantee fees for 
securitized loans, and original term-to-maturity.
    OFHEO chose not to propose CLTV as a criterion for data 
aggregation. Attempting to aggregate data by CLTV would be problematic 
because CLTV value changes throughout the stress period. However, CLTV 
is used to compute important explanatory variables used to predict 
default, prepayment, and severity rates. These variables rely upon CLTV 
to incorporate a loan seasoning process that updates property values at 
the start of the stress test and then throughout the stress period.
d. Property Valuation
    The 1992 Act requires that OFHEO take into account the impact of 
the ``seasoning'' of mortgages on mortgage performance. As that term is 
used in the statute, it requires accounting for changes in LTV due to 
changes in housing values and the repayment of loan principal. 
Accounting for changes in LTVs requires some method of updating 
property values, in addition to computing scheduled amortization. The 
first NPR proposed using the House Price Index (HPI), developed by 
OFHEO, as the basis for updating single family housing values to meet 
the statutory requirement for loan seasoning, in lieu of the Constant 
Quality House Price Index published by the Secretary of Commerce.\72\ 
The HPI, which is published quarterly, provides average house price 
appreciation rates for the nation, the 50 States and the District of 
Columbia, and the nine Census divisions. It uses repeated observations 
of housing values on individual single family residential properties. 
These repeat observations arise where at least two primary mortgages on 
the same property were purchased by either Freddie Mac or Fannie Mae 
since January 1975.\73\ Index values are published starting with 1980.
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    \72\ 61 FR 29616, June 11, l996.
    \73\ The procedures underlying the estimation of the HPI assume 
that individual house price growth rates will be distributed around 
the average growth rate through a log normal diffusion process.
---------------------------------------------------------------------------

    In this NPR, OFHEO proposes the method by which loan seasoning will 
be used to predict credit losses in the stress test, both for single 
family and multifamily mortgages. For single family mortgages, the 
OFHEO HPI is supplemented with various measures of the distribution of 
individual house price growth paths around the average values measured 
by the index. Three terms--dispersion, volatility, and diffusion--are 
important concepts for understanding these measures and how the stress 
test fulfills the statutory requirement that mortgage loans be 
seasoned. ``Dispersion,'' refers to the distribution, at any point in 
time, of the (cumulative) growth rates for values of each house in a 
group, around the average growth rate for that group. Dispersion 
results from ``volatility'' or variability of growth rate paths on 
individual properties from the average growth rate path for all 
properties. Volatility, like dispersion, can be measured through 
statistical relationships. The underlying process by which a model 
generates individual house price growth paths to yield various levels 
of volatility and dispersion over time is called ``diffusion.''
    Similar procedures are used to season multifamily loans, except 
that there is no underlying property value index. Rather, property 
value is estimated using indexes that first update property cash flows. 
Still, the concepts of dispersion, volatility, and diffusion apply to 
multifamily property values, and to the principal measures of borrower 
equity in models of multifamily mortgage performance.
    The ANPR posed several questions related to measurement of house 
price dispersion and to the statistical validity of the HPI as a price 
index. Issues raised by these questions will be discussed below.\74\ 
They are: the appropriate level of geographic aggregation for the HPI 
in the stress test, how to account for the dispersion of house prices 
around the mean in the loan seasoning process, and whether and how to 
adjust for statistical biases and revision volatility inherent in the 
HPI data and estimation methodology.\75\
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    \74\ The first NPR proposed the HPI as the index OFHEO would use 
to season loans in the stress test, but did not address how OFHEO 
would use that index in the stress test. Comments regarding the 
first NPR will be addressed, together with comments on this NPR, 
when OFHEO publishes a final Risk-Based Capital regulation.
    \75\ ``Revision volatility'' refers to changes in previously 
estimated index values that occur as a result of the addition to the 
data of new repeat transaction pairs associated with current 
transactions. Current transactions can change index values for prior 
quarters, because every repeat sale of a property provides 
additional information about house price changes during the time 
since the prior transaction on that property.
---------------------------------------------------------------------------

(i) Geographic Aggregation
    OFHEO's HPI is estimated at the level of individual States and the 
nine Census divisions. A national index is also produced as a 
population-weighted average of the nine Census division indexes. 
Decisions regarding the level of geographic aggregation at which to 
estimate and apply house price indexes

[[Page 18122]]

typically involve a tradeoff between the need to identify relatively 
homogeneous market areas and the need for large enough samples of 
repeat transactions to assure the accuracy of the indexes. This is, 
simply put, a trade-off between the advantages and disadvantages of 
creating indexes for smaller versus larger geographic areas.
    At lower levels of geographic aggregation, both property types and 
the local factors influencing house prices are more likely to be 
similar, and therefore the average appreciation rate is likely to be 
more representative of the trend in individual property values. 
However, lower levels of geographic aggregation result in relatively 
fewer observations for estimation, resulting in increased sampling 
error in the estimated house price index.\76\ At larger levels of 
geographic aggregation, the greater number of observations may yield 
estimates of average price growth with smaller sampling errors, but at 
the risk of not projecting accurately the appreciation rates of the 
various submarkets.\77\
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    \76\ That is, if only a small number of repeat transactions are 
available to calculate a price index, there is a greater chance that 
the resulting index is not representative of price changes in the 
particular housing market as a whole.
    \77\ This situation could occur, for example, if two adjacent 
smaller areas with different rates of appreciation are combined and 
assigned the same average rate of appreciation through a common 
price index. Whether this type of aggregation is ultimately a 
problem depends on how the house price index is to be applied, and 
whether it is to be applied to individual properties or to loan 
aggregates.
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(a) ANPR Comments
    A number of comments were received on the issue of geographic 
aggregation of house price indexes. All commenters implicitly 
recognized the tradeoff involved in choosing the level of geographic 
aggregation. The National Association of Realtors (NAR) recommended 
using the lowest level of market aggregation possible, while at the 
same time minimizing the variance of individual house prices in a 
market area, and urged that the optimum level of aggregation be 
determined by computational considerations. MRAC recommended that the 
choice of aggregation level be driven by objective, external criteria, 
such as minimizing estimation errors, and described its practice of 
using the lowest level of geographic aggregation in constructing its 
indexes, while using higher levels of aggregation for computing the 
variances. Freddie Mac recommended that OFHEO use house price indexes 
computed at the Census division level to avoid the need to rely on what 
it called ``highly uncertain individual house-price volatility 
processes'' that would be associated with the use of a national index 
together with corresponding volatility measures. In addition, when 
compared to State or local level house price indexes, Census division 
level indexes would have lower standard errors and thus more reliable 
predictions.
(b) OFHEO's Response
    The choice of aggregation level of the HPI for the stress test is, 
ultimately, a selection of the level that is most appropriate for the 
seasoning of mortgages when estimating and projecting mortgage 
performance. Because the stress test cannot determine the value of each 
house securing every loan, some type of aggregation is needed. The 
proposed stress test, therefore, combines estimates of average trends 
in house prices with estimates of the dispersion of individual 
appreciation rates around the average growth rate within a given 
geographic area. This approach provides the maximum relevant 
information about the equity position of borrowers.
    After considering the alternatives and the comments, OFHEO believes 
that using HPI indexes computed at the Census division level combined 
with estimates of dispersion of individual appreciation rates around 
the divisional indexes would be appropriate. OFHEO found that available 
data is not sufficient to generate statistically valid State-level 
indexes for some of the less populous States. OFHEO has not proposed to 
use indexes below the State level (at the metropolitan statistical area 
(MSA) level, for example), because there are too few areas in which 
statistically valid indexes can be estimated.
    OFHEO agrees with Freddie Mac's comment that Census division 
indexes without volatility measures reflect regional dispersion better 
than using a national index with such measures. While OFHEO does 
publish State-level HPI series, these series are not statistically 
valid for some of the less populated States. Using Census division 
indexes, in combination with estimates of individual house price 
volatility and the resulting dispersion in each division, provides a 
more complete characterization of housing value dynamics both within 
and across regions.
    MRAC's practice of using a larger level of geographic aggregation 
for volatility estimates than is used for the price index itself is 
appropriate when price indexes are based on very small aggregation 
levels, for example, at the MSA level. Using a larger area to measure 
volatility helps to diminish the small sample problems of generating 
price indexes for very localized markets. However, the same is not true 
when estimating price indexes at the Census division level, because 
there are no small-sample problems at that level of aggregation. 
Furthermore, applying national level volatility to division-level price 
indexes would defeat the purpose of using the division-level indexes. 
National volatility measures of individual house price growth could be 
so large that divisional variations in average house price growth 
become meaningless.
(ii) Volatility and Diffusion
    Choosing to use Census division level price indexes with dispersion 
measures opens additional issues. In particular, capturing the 
dispersion of house price growth rates around an index value requires 
both a measure of volatility and a particular diffusion process to 
translate volatility into actual dispersion. Several ANPR commenters 
addressed these issues in the context of their discussions of 
geographic aggregation.
(a) ANPR Comments
    Comments received in response to the ANPR differed on whether and 
how to estimate the dispersion of individual house-price-appreciation 
rates around the average rates implied by a house price index. Both 
MRAC and the Department of Veterans Affairs (VA) recommended that OFHEO 
use a stochastic (random) diffusion process to allow volatility 
measures to generate a normal (bell-shaped) distribution of individual 
house prices around the mean prices implied by index values. MRAC noted 
that failure to do so would underestimate dispersion, even if a highly 
disaggregated index were used. MRAC observed that underestimation of 
dispersion could cause underestimation of default and severity rates. 
MRAC also stated that the tradeoff between the accuracy of the larger 
sample size and the greater geographic specificity of a smaller sample 
is even more important in estimating the variance (volatility) than in 
constructing the index.
    Both Fannie Mae and Freddie Mac, on the other hand, recommended 
against using a stochastic process to estimate dispersion of house 
values. Freddie Mac argued that one cannot directly observe the 
volatility of house-price growth rates, and that attempts to estimate 
it have thus far failed to achieve adequate consistency. Nor is it 
necessary to estimate volatility, Freddie Mac argued, because the 
variation in house price indexes across Census divisions

[[Page 18123]]

captures a significant amount of the house price dispersion around a 
national house price index, as well as the basic shape of the house 
price distribution for Enterprise loans.
    Freddie Mac also questioned OFHEO's assertion in the ANPR that 
dispersion increases over time. It suggested that models that impose 
increasing dispersion on house price changes, such as ``random walk'' 
models, are inappropriate because long-run market forces keep the 
appreciation of individual houses moving roughly with the national 
average, and because the data do not support such models. Freddie Mac 
asserted that such models systematically overstate dispersion for 
longer holding periods and could significantly and artificially inflate 
the capital requirement.
(b) OFHEO's Response
    OFHEO understands the reason for Freddie Mac's concerns about 
volatility, but notes that Freddie Mac's comments preceded OFHEO's 
first publication of the HPI. Based on its experience in estimating the 
HPI, OFHEO now finds it possible to estimate house-price volatility 
with adequate reliability, particularly for indexes estimated at the 
Census division level. Volatility measures are produced as part of the 
statistical process used to generate the OFHEO HPI. These measures are 
used to summarize the underlying diffusion process and characteristic 
dispersion of house price growth paths as a function of time. The 
volatility measures (parameters) are published in the OFHEO HPI Report. 
They model dispersion as a function of mortgage age. OFHEO preferred 
such a stable process to one that relies on stochastic processes that 
yield different results every time they are used. Because the OFHEO HPI 
volatility parameters are produced with the HPI itself, they provide 
results consistent with the HPI, and they are, therefore, OFHEO's 
choice for capturing house price dispersion in the proposed stress 
test. However, OFHEO agrees with Freddie Mac's concern that estimates 
of dispersion for longer holding periods may be unreliable, and has 
adopted an approach in which estimated dispersion is held at fixed 
levels after mortgages reach a certain age.\78\
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    \78\ This age varies by Census division, but is approximately 15 
years from mortgage origination. The formula for computing the 
maximum allowable age for each Census division can be found in 
section 3.5.2.3.2.3., Probability of Negative Equity 
(PNEQq), of the Regulation Appendix.
---------------------------------------------------------------------------

(iii) Revision Volatility
    Revision volatility primarily affects growth rate estimates for the 
most recent quarters included in the index. This is due to the fact 
that relatively more additional data is added affecting these quarters 
than earlier quarters.
(a) ANPR Comments
    OFHEO received a number of comments in response to the ANPR on 
whether changes in the index resulting from revision volatility should 
be reflected in the stress test and, if so, with what frequency. NAR 
suggested that revisions should be made at the same time OFHEO is 
required to re-estimate the capital standards. In contrast, MRAC 
suggested using a ``chaining method'' \79\ that precludes the need for 
revision to index values for historical periods. The chaining method 
eliminates revision volatility because it does not revise data of 
earlier periods as new data become available. Freddie Mac suggested 
that OFHEO calculate the revisions so as to exploit the greatest 
possible set of information, but moderate the resulting volatility of 
the capital requirement by placing limits on the size of the quarterly 
or annual revisions to the indexes. ACB argued for a reasonable advance 
notice to the Enterprises prior to any changes in the capital 
requirement resulting from changes in the indexes to enable them to 
engage in reasonable business planning.
---------------------------------------------------------------------------

    \79\ The chaining method involves the following steps: (1) 
estimation of a historical reference index using all repeat 
transactions data available as of a specified date, after which no 
revisions in previously estimated index numbers will occur; (2) 
acquisition of new data providing information on the most recent 
time period, and including additional repeat transactions that pair 
with transactions in previous periods; (3) application of the most 
recently updated index series to inflate the first property value 
for a repeat transaction pair to update this value to the 
penultimate (next-to-last) time period; and (4) estimation of the 
index number for the last time period using the pseudo-repeat 
transactions data created in steps (1)-(3).
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(b) OFHEO's Response
    The proposed stress test does not include an adjustment for 
revision volatility. Since the time the issue of revision volatility 
was raised in the ANPR, OFHEO has determined that revision volatility 
is not likely to have a significant impact on risk-based capital. 
Revision volatility primarily affects growth rate estimates of the most 
recent quarters, which will be those immediately preceding the start of 
the stress test. For loans that have been outstanding for several years 
at the start of the stress test, changes in appreciation rates in the 
most recent quarters will represent a small proportion of the total 
change in housing values since origination. For loans that have been 
outstanding only a short time at the start of the stress test, 
projected changes in house prices and in LTV will be minimal in any 
case, due to the fact that little time has elapsed since origination, 
and quarter-by-quarter appreciation rates are generally small. 
Consequently, OFHEO does not expect revision volatility to affect risk-
based capital requirements. OFHEO also proposes not to revise the house 
price index used to determine the appreciation rates applied in the 
stress period. Rather, HPI values, as published in the 1996, third 
quarter, HPI Report, will be the basis for relating stress test 
economic conditions to the benchmark experience.
    OFHEO chose not to propose the chaining method suggested by MRAC 
because it fails to use all of the available data in estimation. In 
particular, the chaining method uses information on recent property and 
mortgage transactions only for calculating appreciation rates in the 
most recent period, ignoring the information provided by these 
transactions on appreciation rates in earlier periods.
(iv) Statistical Biases
    In the ANPR, OFHEO requested comment on whether the HPI should 
include adjustments for identifiable sources of statistical bias, on 
how sample selection bias should be addressed,\80\ on whether a 
statistical adjustment should be made to address appraisal bias,\81\ 
and on what additional sources of statistical bias exist and how they 
might be addressed. In NPR1, OFHEO stated that it would make no

[[Page 18124]]

adjustments to the HPI itself, but would discuss in the second NPR 
whether such adjustments were to be made in the stress test.
---------------------------------------------------------------------------

    \80\ Sample selection bias refers to the possibility that using 
repeat transactions as the selection criteria, rather than random 
selection, could result in an index that is biased. Selection bias 
results when the probability that a property does or does not repeat 
is correlated with the change in value. For example, bias can result 
when the period between transactions is correlated with the change 
in house prices. Because more rapidly appreciating properties turn 
over within shorter time intervals, they are more likely to appear 
in the sample used for estimation. In addition, properties that are 
sold or refinanced are likely to be the ones that have had higher 
than average appreciation.
    \81\ Appraisal bias can result from the perceived tendency of 
appraisers, as agents of primary mortgage lenders, to impart an 
upward bias to a home value to insure that a home sale is made. 
Appraisal bias also occurs when the use of appraisals to value 
property at refinancing may smooth the fluctuations in housing 
values because appraisals are derived from comparisons with 
properties that have either been sold or listed for sale within the 
past several months and may fail to indicate more recent changes in 
housing value. In fact, listings are only used in case circumstances 
where actual sales are few and far between, most often in rural 
areas.
---------------------------------------------------------------------------

(a) ANPR Comments
    As a general comment, Freddie Mac cautioned that research on 
potential sources of bias is relatively new and that attempting to 
``un-bias'' future price index values estimates introduces a high 
degree of complexity. Consequently, Freddie Mac recommended keeping the 
house price index simple until research on potential bias is more 
conclusive. Freddie Mac also suggested that the reliance of the 
weighted repeat sales technique on the ordinary least squares (OLS) 
method \82\ may result in bias because that methodology does not 
generally provide robust estimates of central tendencies in the 
presence of outlier observations, where appreciation is especially 
large or small. Freddie Mac suggested eliminating outliers or ``down-
weighting'' them, for example, by using a median regression.
---------------------------------------------------------------------------

    \82\ Ordinary least squares is the most commonly used 
statistical technique for simultaneously analyzing the relationship 
of many explanatory variables to one special variable of interest 
(called the ``dependent'' variable).
---------------------------------------------------------------------------

(b) OFHEO's Response
    OFHEO agrees with Freddie Mac that attempts to adjust the HPI would 
be premature and should await more conclusive research. OFHEO also 
agrees with Freddie Mac's general observation on the sensitivity of OLS 
estimates to outliers, but has concluded that adopting another 
estimation methodology is unwarranted. It should be noted that the 
weighted-repeat sales (WRS) methodology \83\ applied to estimate the 
OFHEO HPI uses information obtained from a first-stage OLS estimation 
to develop weights that have the effect of discounting the impact of 
transactions that occur far apart in time. Because these are the 
transactions that are presumed under the WRS method to have the largest 
sampling variability, and therefore those most likely to contribute 
outliers, the WRS method automatically accounts for the potential 
impact of outliers. In addition, OFHEO reports median rather than mean 
appreciation rates, which diminishes any potential impact of outlier 
data.\84\
---------------------------------------------------------------------------

    \83\ This methodology, which is explained in the first NPR, uses 
pairs of transactions (i.e., repeat sales) involving the same homes 
to estimate home price appreciation.
    \84\ The WRS methodology used to generate the OFHEO HPI actually 
computes median growth rates, directly. These rates need to be 
adjusted to compute mean growth rates. In NPR1, these were referred 
to as geometric and arithmetic means, respectively.
---------------------------------------------------------------------------

(v) Sample Selection Bias
    Repeat-sales and repeat-transaction price indexes do not include 
property value information from all mortgage transactions. Issues of 
potential bias in the measured house price appreciation rates arise 
because the sample of properties on which repeated transactions are 
available may not be fully representative of all properties in a given 
market area.
(a) ANPR Comments
    A number of comments were received on sample selection bias in 
generating a house price index. Freddie Mac noted that sample selection 
bias results from using only properties that have been sold or 
refinanced. The selection of these properties is not random and is 
correlated positively with price appreciation. That is, properties with 
lower rates of appreciation will have fewer sales and refinancings, and 
thus provide relatively fewer observations for calculation of the HPI. 
Although Freddie Mac recommended that this issue be addressed by using 
a WRS index, which provides retrospective information by pairing two 
transactions on the same property at different time periods, it noted 
that some sample selection bias is present in the near term.
    NAR suggested that sample selection bias results from the movement 
of an individual property from government mortgage insurance programs 
(Federal Housing Administration (FHA) VA) into the conforming 
conventional market, and vice versa, because the lower property values 
captured in the government insurance and guaranty programs might not be 
matched in the WRS series. If price appreciation in a market area is 
distributed unevenly with respect to selling price (i.e., lower priced 
homes appreciate slower or faster than do higher priced homes), the 
absence of a match at the lower end may introduce a bias in the level 
of price appreciation for the market under evaluation. NAR suggested 
that using FHA data, to the extent it is available, to construct the 
weighted repeat sales transactions, would adjust for the low-end sample 
selection bias. NAR also suggested that OFHEO investigate using 
different criteria with respect to time between repeat transactions 
entering the Enterprise loan history file to determine if the end of 
sample bias is significant, and to possibly suggest ways of correcting 
for it. NAR suggested that one way of correcting for any such bias 
would be to restrict the repeat sales in the sample to three-, five-, 
and seven-year matches and to evaluate the level of bias that results.
    ACB suggested that the effect of sample selection bias resulting 
from the tendency to have greater turnover in that part of the housing 
stock in which price appreciation has been stronger could be determined 
by a separate analysis of the relationship between a foreclosure 
property index and the overall price index. MRAC suggested that some 
bias might result from properties leaving the sample because they have 
appreciated enough that the size of subsequent mortgages on those 
properties is above the conforming loan limit. MRAC then suggested that 
indexes built on Enterprise data be compared to other more broadly 
constructed indexes, such as those estimated by MRAC, that include all 
properties that initially meet the conforming limit. MRAC also 
suggested that the incidence of default and expected losses would be 
underestimated if the impact of junior liens were not taken into 
account.
(b) OFHEO's Response
    OFHEO believes that no adjustments are necessary to correct for 
potential sample selection bias. Low-end sample selection bias due to 
the exclusion of FHA loans should not have a significant impact on the 
HPI. FHA loans do not represent the entire lower end of housing 
markets. There is ample representation of lower valued loans and 
properties in the data used to estimate the HPI, in part because the 
Enterprises promote affordable lending and are subject to HUD 
affordable lending regulations. Furthermore, although FHA eligibility 
requirements have historically been less restrictive than conventional 
lending requirements, current trends in conventional lending are toward 
more flexible standards, including lower down-payment requirements.
    Although OFHEO agrees with MRAC that the conforming loan limit may 
itself produce some bias in repeat transactions index values, this bias 
is not significant in the HPI. Bias resulting from the conforming loan 
limit would occur in high-cost housing markets where there are 
significant numbers of homes with values near the conforming loan 
limit, and where appreciation rates are greater than the national 
average. As home values and loan amounts increase in these areas, new 
loans may no longer be eligible for purchase by the Enterprises, and 
the property appreciation cannot be captured in the HPI. However, such 
bias would occur only in very isolated instances. First, the conforming 
loan limit is substantially

[[Page 18125]]

above the average home price in nearly all areas of the country. The 
loan limit would only create a significant issue for the stress test if 
OFHEO were to use State, rather than Census division, indexes. The 
potential in particular States with high-cost metropolitan areas for 
sample selection bias resulting from the conforming loan limit becomes 
less relevant when the HPI is estimated at the Census division level. 
Second, the loan limit is updated annually by a factor representing 
national house price appreciation.\85\ Third, borrowers may obtain two 
mortgages on a property in order to take advantage of the interest rate 
advantages of having a first mortgage under the conforming limit. In 
that situation, repeat transactions are captured by the HPI even if the 
total amount of mortgages on a property exceeds the conforming loan 
limit. All of these factors suggest that the conforming loan limit is 
not a significant source of bias in the OFHEO HPI.
---------------------------------------------------------------------------

    \85\ The conforming loan limit is administered by the Federal 
Housing Finance Board.
---------------------------------------------------------------------------

(vi) Appraisal Bias
    Because interest rates have generally fallen since the early 
1980's, most of the mortgage transactions used in estimating the HPI 
are refinancings, rather than loans for home purchase. This fact raises 
the question of the consistency between actual prices recorded on 
purchase-money mortgages and appraisals used for refinance mortgages.
(a) ANPR Comments
    Several comments on appraisal bias were received. Freddie Mac 
recommended against using a statistical adjustment to the HPI to 
address the impact of appraisal bias, asserting that it is far from 
clear whether indexes based solely on purchase prices, versus those 
based on a combination of purchase prices and appraisal values, better 
represent true house-price appreciation rates. Freddie Mac asserted 
that the common notion that purchase price is the ``true'' price is a 
misconception, since the purchase price is but one of a distribution of 
potential prices for any given house at any time. In light of the 
current uncertainty over the extent of the bias, Freddie Mac believes 
that it would be premature for OFHEO to attempt to develop a model to 
correct for it.
    MRAC suggested that eliminating transactions in which an appraised 
value is used for either ``sale amount'' in the matched pairs would be 
desirable, but may not be practical. MRAC cited its own research to 
suggest that appraisal bias causes the yearly price appreciation 
measured by transaction-based indexes to be one percentage point too 
high. ACB suggested that construction of house price indexes with and 
without refinance transactions would permit an assessment of about 
whether appraisal bias is a significant phenomenon.
(b) OFHEO's Response
    OFHEO agrees with Freddie Mac's recommendation that adjustments in 
the HPI for potential appraisal bias not be made. Issues of statistical 
bias merit further research and analysis, but at the present time OFHEO 
is aware of no better alternative index to use in the stress test. 
Also, measuring HPI only on actual purchase prices would compromise the 
statistical reliability of the indexes over time, because the majority 
of property values used in generating the various HPI indexes come from 
refinancing transactions, using appraisal values.
    In response to MRAC's comment on appraisal bias in appreciation 
rates, it should be noted that the mere existence of identifiable 
differences due to use of appraisals does not outweigh the overall 
benefit of using the HPI in the stress test. Further, it is unlikely 
that any appraisal bias that may exist in the HPI would have a 
meaningful effect on risk-based capital because of the way in which the 
HPI is used in the stress test. The mortgage performance models in the 
stress test rely upon statistical equations that relate explanatory 
variables developed using the historical HPI to actual, historical 
mortgage performance. The same historical HPI series is used to season 
(update LTVs of) existing loans to the start of the stress period. 
Using the same HPI series to estimate the statistical model and to run 
the stress test eliminates the effect of any appraisal bias in the HPI 
on default and prepayment rates in the stress test.\86\
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    \86\ Appraisal bias could, theoretically, affect the rates 
generated by the stress test if the method of computing the HPI were 
changed in some way to account for appraisal bias or if appraisal 
bias were found to be significantly different in more recent data 
than in the historical data used to estimate the models. OFHEO does 
not believe the change in the amount of appraisal bias in the HPI, 
if any, is significant.
---------------------------------------------------------------------------

(vii) Multifamily Loans
    For multifamily loans, OFHEO does not propose to use the HPI or any 
other repeat-sales or repeat-transaction index to update property 
values. There is not enough data available for OFHEO to develop its own 
price index, and the only known price indexes blend many commercial 
property types, have small numbers of observations, and are national in 
scope. To overcome these data problems, OFHEO proposes to use an 
earnings-based method for updating property values.
    Multifamily loans are commercial loans for which property value 
depends upon the stream of earnings generated by the property. For 
these loans, OFHEO proposes to base the property value on earnings 
multiplied by a price-to-earnings capitalization factor. The 
capitalization factor summarizes the present value of a stream of 
expected future earnings for a given property, using current interest 
rates at each month of the stress test to discount the expected 
earnings stream. Earnings are a function of net operating income at 
loan origination, rental inflation, and the change in vacancy rates 
since loan origination. The proposed stress test updates the price-to-
earnings capitalization factors as a function of changes in interest 
rates, holding property-specific characteristics constant. In this way, 
the stress test updates property values and seasons multifamily loans 
in the proposed stress test.
    In choosing the actual rent growth and vacancy indexes used to 
update property earnings over time, OFHEO used government data where 
available. Government data were available for all statistical analysis, 
and for seasoning loans to the start of the stress test. In particular, 
the model performs the statistical analysis and the seasoning of 
existing loans to the start of the stress test using the rental cost 
component of the Bureau of Labor Statistics Consumer Price Index (CPI) 
to create a geographic specific rent index. Vacancy rates are not 
needed for pre-stress period seasoning, but are used in estimating the 
statistical model. The series used is the rental property vacancy 
series published by the Bureau of the Census (Census Vacancy 
Series).\87\ Because Enterprise purchases of multifamily loans are 
heavily concentrated in MSAs, MSA indexes are used, where available, to 
update property values.
---------------------------------------------------------------------------

    \87\ The CPI and Census Vacancy Series are both based on single 
and multifamily rental properties. OFHEO believes that the inclusion 
of single family rental properties in the samples used to calculate 
vacancy rate and rent growth rate series is not a serious concern 
for the stress test. These series capture the cyclical dynamics of 
multifamily rental markets, and are useful for updating property 
values before and during the stress period.
---------------------------------------------------------------------------

    Government data are not available for the entire stress period 
itself. As explained later in the discussion under section III. A.7., 
Relating Losses to the Benchmark Loss Experience, the stress

[[Page 18126]]

test links stress period losses to the benchmark experience in part by 
specifying benchmark rates of property value appreciation. However, CPI 
rental cost data is not available for the benchmark time and place, and 
Census Vacancy Series rates are only available for the benchmark 
experience starting in 1986. To deal with this absence of government 
data, OFHEO created a rent index consistent with the CPI data, but 
based upon apartment data available from the Institute for Real Estate 
Management (IREM). To fill in benchmark experience vacancy rates for 
1984-1985, OFHEO also used IREM vacancy data to estimate the Census 
Vacancy Series. The estimated government series are consistent with the 
data used to estimate the mortgage performance models and season the 
loans prior to and during the stress period itself.
    Volatility estimates for rental rate inflation and vacancy rates 
are used to calculate the dispersion of multifamily property values, in 
much the same way volatility measures for the HPI series are used to 
measure dispersion of property values for single family loans.
5. Default/Prepayment Issues
a. Use of Conditional Default and Prepayment Rates
    A threshold issue for OFHEO was whether to construct statistical 
models of conditional rates of loan defaults and prepayments or to 
adopt a less detailed approach, such as calculating only cumulative 
rates and distributing them in fixed percentages across the ten years 
of the stress test. A conditional rate of default or prepayment refers 
to the volume of loans that default or prepay during any period, 
expressed as a percentage of the total volume of loans surviving at the 
start of that period. The term ``surviving loans'' means those from the 
group that have not previously prepaid or defaulted. A cumulative rate 
of default or prepayment is the total percentage of a group of loans 
that default or prepay during the entire period being studied (such as 
the ten-year stress period). A group of loans studied over a ten-year 
period would have a single cumulative default rate, but would have ten 
annual conditional default rates.
(i) ANPR Comments
    The ANPR asked whether default rates should be expressed in terms 
of conditional failure rates, cumulative default rates, or in some 
other manner. In response, MRAC stated that ``[d]efault rates are best 
measured by cumulative life-of-loan rates with conditional rates for 
each time period determined by estimating `seasoning curves' similar to 
the Standard Default Assumption of the Public Securities Association 
(PSA) \88\.'' ACB's comments, which emphasized the importance of 
modeling the shrinking population of loans exposed to the credit risk 
in the declining rate scenario, assumed that a conditional rate 
approach should be used. Similarly, a preference for conditional rates 
of default and prepayment is also implicit in NAR's assertion that the 
principal merit of using a joint default/prepayment model is that it is 
capable of using all available information to determine whether a 
mortgage survives from one year to the next.
---------------------------------------------------------------------------

    \88\ PSA has subsequently changed its name to the Bond Market 
Association. The PSA Standard Default Assumption is to allow monthly 
conditional rates to increase from zero to some peak rate over the 
first 30 months of mortgage life, to hold that peak rate constant 
for another 30 months, and then to allow monthly rates to decline 
for an additional 60 months. The final rate reached at the end of 
120 months is held constant throughout the remaining life of the 
loans (Public Securities Association, Standard Formulas for the 
Analysis of Mortgage-Backed Securities and Other Related Securities. 
New York: Public Securities Association, update No.7, June 29, 1993, 
at SF-14.).
---------------------------------------------------------------------------

    Freddie Mac and Fannie Mae, however, recommended using cumulative 
default rates to simplify the analysis. Freddie Mac was concerned that 
conditional prepayment rates would lead to absurdly high default rates 
in an up-rate stress test. In the up-rate scenario, prepayment rates 
would be low, more loans would be outstanding, and default rates 
conditioned on the number of loans outstanding would result in more 
defaults. Freddie Mac recommended using actual cumulative default rates 
from the worst region, which, implicitly, would include the same 
prepayment effect as that which occurred during the benchmark period.
(ii) OFHEO Response
    OFHEO proposes to apply statistical models of conditional rates of 
default and prepayment for both single family and multifamily mortgages 
in the stress test. The advantages of this approach are numerous. The 
proposed approach automatically accounts for the impact of defaults on 
the number of loans remaining active and subject to the risk of 
prepayment, and vice versa. This feature is essential to develop a 
reasonable representation of Enterprise mortgage cash flows across the 
different economic scenarios envisioned by the stress test. It also 
avoids potential numerical anomalies that might arise when total or 
annual defaults during the stress test are fixed, such as years in 
which total defaults would exceed total surviving loans due to high 
prepayment levels in the declining-rate scenario of the stress test. 
Also, the periodic nature of mortgage payments, scheduled amortization, 
and the coupon adjustments on adjustable rate loans, all of which 
affect mortgage performance, require a model that reflects a discrete 
time period for each default or prepayment event.
    OFHEO believes that a statistical model of conditional defaults and 
prepayments is more accurate and more sensitive to stress test economic 
factors, and to the Enterprises' starting books of business, than are 
simpler methods that might be developed. Each quarter the test is 
applied, a statistical model can account for changes in economic 
conditions (such as the level and shape of the Treasury yield curve or 
recent trends in house prices) and the composition of an Enterprise's 
business since the last time the test was performed. That is, the rates 
of default and prepayment applied when the stress test is run are 
adjusted to reflect current circumstances. Such adjustments are 
particularly important because mortgage prepayment and default rates 
are highly time-dependent, characteristically increasing during the 
first years following origination, peaking sometime between the fourth 
and seventh years, and declining over the remaining years. However, 
this time-characteristic pattern is itself affected by economic 
conditions.
    Another advantage of modeling conditional default and prepayment 
rates is the support this approach provides for the proper treatment of 
loss severity. Loss severity is affected significantly by factors that 
affect the timing and amount of defaults in the stress test. Loss of 
loan principal balance, the single largest cost element in determining 
loss severity, is dependent upon house price declines, which are 
dependent upon economic conditions leading up to the date of default. 
Funding costs are also affected by the changing interest rates in the 
stress test, as explained in later discussions under section III. A. 
6., Loss Severity. For all of these reasons, using conditional default 
and prepayment rates during each month of the stress period greatly 
improves the sensitivity of the stress test to risk factors.
    The proposed approach is, overall, responsive to concerns raised in 
the ANPR comments, although OFHEO has proposed models of conditional 
rates of default and prepayment, rather than accept the recommendation 
of several commenters to use cumulative rates. NAR and ACB recommended 
use of

[[Page 18127]]

conditional rates. As ACB recognized, the stress test must account for 
the shrinking population of loans exposed to credit risk in the 
declining rate scenario. Only through the application of conditional 
default and prepayment rates is it possible to account for this 
shrinking population under the alternative interest rate scenarios of 
the stress test.
    MRAC recommended measuring cumulative life-of-loan rates with 
conditional rates for each time period determined by estimating 
``seasoning curves'' similar to the Standard Default Assumption of the 
Public Securities Association to determine conditional rates. OFHEO 
proposes a model with much the same features suggested by MRAC. This 
model uses mortgage age in the statistical default equations to provide 
a baseline default rate time-series analogous to the PSA assumption. 
(See note 41, infra.) That baseline is scaled, or multiplied upward, in 
the same way that PSA recommends using its baseline curve, when the 
stress test adjusts or ``calibrates'' its statistical default equations 
to relate them to the benchmark experience. (See section III. A. 7., 
Relating Losses to the Benchmark Loss Experience.)
    OFHEO's approach is also responsive to the recommendations of 
Fannie Mae and Freddie Mac to keep the models simple. OFHEO proposes to 
minimize the number of explanatory variables and to create as much 
consistency as possible across different mortgage types while still 
capturing differential credit risk by mortgage type. The models are 
also ``simple'' in that the mortgage performance equations used in the 
stress test can be used by the Enterprises--without any modifications-
to replicate the stress test. Further, OFHEO believes that using 
cumulative default rates would not achieve significant simplification. 
Freddie Mac's comments recognized that default and prepayment rates are 
not uniform among loans with different characteristics. To deal with 
these important differences, Freddie Mac suggested developing a system 
of multiples and LTV categories that would be applied to historical 
cumulative default rates. However, this approach requires a matrix of 
rates that becomes, in practice, more complicated to estimate than a 
statistical model of conditional default rates. Therefore, developing a 
statistical model, based upon well-recognized techniques that are 
widely used in the mortgage industry, was, in OFHEO's view, a 
preferable approach.
b. Identifying Events for Default and Prepayment
    A practical issue for modeling default and prepayment rates is how 
to identify a default or prepayment event in the historical Enterprise 
data.
(i) ANPR Comments
    A number of ANPR commenters, including MBA and Freddie Mac, 
suggested defining default events only in terms of foreclosures, 
because many delinquencies are cured and do not generate significant 
losses. In contrast, the VA suggested modeling the timing of cash flows 
associated with all delinquencies, including loans that are reinstated 
and do not terminate.
    Only Freddie Mac addressed the subject of curtailments as a form of 
prepayment. Curtailments are partial prepayments, made in addition to 
regularly scheduled mortgage payments. Freddie Mac did not suggest that 
they be tracked as mortgage events, but only that some consideration of 
them be given in the calculation of current LTV ratios to account for 
the resulting improvements in borrower equity positions. Freddie Mac 
cited a study on Ginnie Mae curtailment speeds,\89\ and suggested that 
Enterprise loan pools might have higher rates of curtailment than found 
in the study, because of better borrower equity and liquidity 
positions.
---------------------------------------------------------------------------

    \89\ Peter Chinloy, ``Elective Mortgage Prepayment: Termination 
and Curtailment,'' Journal of the American Real Estate and Urban 
Economics Association 21 (3, Fall 1993), 313-332.
---------------------------------------------------------------------------

(ii) OFHEO Response
    OFHEO agrees with MBA and Freddie Mac that the stress test should 
not consider all delinquencies to be defaults. Only delinquencies that 
result in termination of the loan are treated as defaults in the stress 
test. Historically, these events predominantly have been foreclosures, 
although today these events also include pre-foreclosure sales, where 
delinquent borrowers sell their properties before foreclosure and share 
the losses with the Enterprise and/or mortgage insurer.\90\ OFHEO found 
that the more detailed modeling of delinquencies suggested by the VA 
would make the model more complex and would not have a significant 
impact on risk-based capital. The impact would be minimal, because in 
the time and place of the benchmark loss experience, few, if any, 
alternatives to foreclosure were utilized by the Enterprises and the 
benchmark rates would, therefore, not change. Also, even if modest 
improvements to the stress test were possible by modeling delinquency 
events, at this time there are insufficient data to support an analysis 
of delinquency resolutions and costs.
---------------------------------------------------------------------------

    \90\ A less important default termination event is the transfer 
of the property deed, in lieu of foreclosure. This is a foreclosure-
like event in that it results in the Enterprise taking title to the 
property and having to manage and sell it, just as is the case with 
foreclosed properties.
---------------------------------------------------------------------------

    Mortgage default and prepayment events result from a borrower's 
decision to terminate the mortgage, either by prepaying or defaulting, 
resulting in an observed last-paid installment, after which no further 
payments are forthcoming. In the case of (full) mortgage prepayment, 
the borrower terminates the loan by repaying the remaining principal 
and any outstanding interest. The models identify prepayment events in 
the Enterprise data by the existence of a last-paid installment date 
and a change in the loan status from active to prepay. Loan defaults 
are identified as any loan that has terminated without an indication 
that it has been prepaid or paid off at maturity.
    In the proposed stress test, curtailments made prior to the 
beginning of the stress period are accounted for in the starting loan 
balances reported to OFHEO from the Enterprises. OFHEO does not, 
however, propose giving further consideration for potential 
curtailments in the stress period itself. OFHEO has found no evidence 
that curtailments have a significant impact on current LTVs of 
Enterprise loans on a portfolio-wide basis.\91\
---------------------------------------------------------------------------

    \91\ The Chinloy study cited by Freddie Mac, which used a 
limited data set, found that curtailments in the study period 
(January 1988-May 1989) amounted to a very small rate (0.42 percent 
per year) on the outstanding loan balances of the Ginnie Mae 
security pools. Ibid., p. 326. More recent work by Fu, Lacour-
Little, and Vandell, on conventional mortgage curtailment rates, 
also shows that curtailments amount to a small percentage of 
portfolio balances. Qiang Fu, Michael Lacour-Little, and Kerry 
Vandell, ``Retiring Early: an Empirical Analysis of the Mortgage 
Curtailment Decision,'' unpublished manuscript, University of 
Wisconsin--Madison, December 1997. These authors observed 25,566 
mortgages for a 21-month period. These included a mixture of 
conforming and jumbo loans, and included loans originated from 1967 
to 1995. During a 21-month observation period, these authors found 
that over 86 percent of the loans surveyed made no curtailments, and 
only 0.64 percent of the loans made curtailments in excess of one 
percent of the original loan balance. Ibid, Table 3, p. 22. The 
largest curtailments were made on older loans (close to 20 years 
old), where loan balances and default rates will be small to begin 
with. Thus, any effect of these curtailments on credit losses would 
be insignificant for risk-based capital determination.
---------------------------------------------------------------------------

c. Use of Joint Default/Prepayment Models
    A key issue raised in the ANPR was whether to use a joint 
prepayment and

[[Page 18128]]

default model or some simpler assumptions about default and prepayment 
rates in the stress test. In the ANPR, OFHEO also asked whether 
prepayments during the stress test should affect the volume or timing 
of defaults.
(i) ANPR Comments
    Several commenters supported the use of a joint model of defaults 
and prepayments. MRAC stated that the ``absolute merits'' of the 
approach are ``obvious.'' NAR asserted that the principal merit of 
using a joint model of conditional default and prepayment probabilities 
is its ability to use all the available information to determine 
whether a mortgage survives from one year to the next or is lost from 
the portfolio through prepayment or default. HUD cited the need to 
model defaults and prepayments together as simultaneous decisions based 
on the underlying property equity.
    The Enterprises opposed a joint default and prepayment model. 
However, Fannie Mae, although not recommending joint modeling, noted 
the interrelationship between defaults and prepayments. Fannie Mae 
favored the use of a statistical model that would determine only total 
terminations (prepayments plus defaults) in each of the two stress test 
interest rate scenarios. Fannie Mae suggested that total defaults in 
both scenarios be set at the levels that occurred in the benchmark loss 
experience. Prepayments would be calculated by subtracting total 
defaults from total terminations. Fannie Mae made no specific 
recommendation about how conditional default rates might be determined 
or how total defaults and prepayments should be distributed through the 
stress period. Fannie Mae opined that the methodology it recommended 
would be consistent with the 1992 Act and would provide a workable 
framework for capturing the relationship between defaults and 
prepayments. Fannie Mae also viewed this approach as consistent with 
industry practice and asserted that it would be easier for the company 
to manage to a capital standard based upon such an approach than it 
would be to manage to one based upon a joint statistical model.
    By contrast, Freddie Mac, while preferring a simpler approach to 
default modeling, asserted that a joint statistical model of default 
and prepayment rates would be preferable to total termination models in 
the stress test context because: (1) unlike the total terminations 
models, the joint model ensures that defaults and prepayments ``add 
up'' to the total mortgage terminations; (2) total termination models 
focus on interest rate movements under the assumption that default is a 
small part of terminations under normal conditions, (an assumption 
Freddie Mac found unwarranted in a stress test environment); and, (3) 
standard termination models capture small effects such as seasonal 
variation, which would unnecessarily complicate the stress test.
    Freddie Mac also favored an empirically based statistical model of 
mortgage performance over a stochastic simulation model like those used 
in mortgage-backed security pricing. Freddie Mac stated that stochastic 
models are not typically used by the industry for default and 
prepayment modeling because borrower housing objectives are too complex 
and heterogeneous to be described adequately with a single set of rules 
simple enough to solve analytically.
    Although Freddie Mac favored the use of a joint statistical model 
over these other approaches, Freddie Mac did not recommend that OFHEO 
use one in the stress test, asserting that OFHEO would have difficulty 
using the data from the benchmark experience to estimate the model. 
Freddie Mac also cited the need to model prepayments during the stress 
period as a function of current coupons and interest rates. Freddie Mac 
instead recommended estimating a statistical equation for prepayments 
based on historical data from a distressed region to factor prepayments 
into the stress test. Freddie Mac asserted that this approach would 
allow implementation of the two interest-rate scenarios while tying 
prepayment rates to the benchmark experience. Freddie Mac also 
recommended using cumulative default rates from the benchmark 
experience as the stress test default rates.
    Freddie Mac raised other issues about joint models, claiming that 
they are not ideal because: (1) they are complex; (2) they require 
assumptions about both house price drift (average appreciation) and 
volatility (variation in individual appreciation rates around the 
average rate); (3) they require assumptions as to what constitutes 
negative equity; and (4) they require other factors, such as loss of 
employment to be modeled.
(ii) OFHEO's Response
    OFHEO proposes to use joint statistical models in the stress test 
for both single family and multifamily loans, agreeing with 
recommendations of many commenters. Also, OFHEO found that total 
termination models, such as those recommended by Fannie Mae, were not 
adequate for the purposes of the proposed regulation. (See earlier 
discussion under section III.A.5.a., Use of Conditional Default and 
Prepayment Rates.) As explained in the ANPR, prepayments have a major 
impact on cumulative and conditional rates of default, because every 
loan that prepays is one less loan that could later default. However, 
high levels of prepayment, which occur when interest rates decline, can 
also result in increased conditional default rates in periods that 
follow. This phenomenon, referred to as ``adverse selection'' or 
``burnout,'' occurs because loans that do not prepay when interest 
rates decline are often lower quality loans that do not qualify for 
refinancing. Using a joint default/prepayment model allows the stress 
test to reflect the impact of prepayments (and, therefore, of interest 
rate changes) upon defaults.
    The joint modeling approach is based on well-known and accepted 
statistical methods that are widely applied in the mortgage performance 
research. Researchers have found multivariate statistical models to be 
necessary for this research, because the borrower's options to default 
or prepay are interrelated. OFHEO believes that simpler approaches 
(models or tabulations) that fail to account for this complexity would 
not provide reasonable and appropriate projections of mortgage 
performance during the stress period.
    OFHEO addressed Freddie Mac's concern about the difficulty of 
retaining a reasonable relationship to the benchmark loss experience in 
a joint model by: (1) replicating certain benchmark economic factors--
specifically, house prices, rent growth rates and rental vacancy 
rates--in the stress test; and (2) adjusting the underlying default and 
severity equations used in the stress test to allow them to replicate 
exactly the benchmark experience. Modeling the effects of differences 
in starting coupons and interest rates from the benchmark loss 
experience was possible, because OFHEO's database allowed the models to 
be estimated based upon a broad and representative sample of historical 
mortgage performance data. The statistical equations therefore yield 
reasonable estimates that can be used to project mortgage prepayment 
under many different circumstances, including stress test interest rate 
scenarios.
    Regarding the issue of model complexity, in OFHEO's view, the 
proposed models strike the appropriate balance between accuracy and 
simplicity. The stress test uses an approach based on well-known and

[[Page 18129]]

accepted statistical methods that are applied and accepted widely in 
academic research and in industry practice. Further, OFHEO has 
developed specifications for the default and prepayment models that 
avoid unnecessary complexity. The prepayment model suggested by Freddie 
Mac--using Freddie Mac projections from a statistical equation with ad 
hoc adjustments based on mortgage coupon rates--is at least as complex, 
but far less accurate.
    As to house price appreciation and volatility, any model of 
mortgage performance includes, explicitly or implicitly, assumptions 
about these factors. OFHEO believes that the proposed stress test 
includes a reasonable and appropriate methodology for updating house 
prices throughout the stress period. (See section III.A.4.d., Property 
Valuation.)
    OFHEO does not agree with Freddie Mac that the need to use 
assumptions about negative equity to estimate a joint model is a reason 
not to use a joint model. Any statistical model of mortgage default 
requires certain assumptions about how to measure negative equity in 
order to predict defaults. Although expected equity values cannot be 
assigned to individual borrowers to determine a precise LTV for each 
loan, using probabilities of negative equity provides substantial 
information about the negative equity position of individual borrowers. 
The probability of negative equity is a function of the current loan 
balance and the probability that individual house prices are below that 
balance. It is especially valuable when modeling the default potential 
from groups of loans, as is the case in the proposed stress test. By 
applying estimates of house price drift and volatility obtained from 
independent estimates based on the OFHEO House Price Index, the 
distributions of individual housing values relative to the value at 
mortgage origination are determined. This approach eliminates the 
measurement difficulties associated with calculating individual 
borrower equity at the loan level.
    The concern that developing a statistical model for the stress test 
would require modeling the effects of unemployment on prepayment rates 
does not raise an issue, because OFHEO does not propose to use 
unemployment as an explanatory variable in the stress test. In general, 
OFHEO has limited the explanatory variables in the stress test to those 
that define different loan characteristics or product types are 
required to meet statutory requirements. As explained above in section 
III.A.2., Overview of Mortgage Performance, OFHEO has avoided 
variables, such as unemployment, that require assumptions about stress 
period economic conditions that are not specified in the 1992 Act. (See 
section III.A.5.e., Choice of Explanatory Variables for Default and 
Prepayment).
d. Choice of a Statistical Method for a Joint Model of Default and 
Prepayment
(i) ANPR Comments
    The ANPR sought comment on the appropriate statistical method to 
use for a joint model of default and prepayment. None of the ANPR 
comments provided an express recommendation of a model, but NAR 
supported a multivariate model and suggested that the proportional 
hazard model developed by John Quigley and Robert Van Order in 1992 
would provide a good starting point. Other commenters, such as Freddie 
Mac and ACB, emphasized that any joint model must be robust and able to 
yield reasonable results under many different scenarios.
(ii) OFHEO Response
    OFHEO agrees with the NAR comment that proportional hazard models 
provide a good starting point. These models measure conditional rates 
of default and prepayment. The stress test utilizes a similar approach, 
the logit model, which is more appropriate for large data sets. OFHEO 
also agrees with Freddie Mac and ACB that a joint model should be 
robust and able to yield reasonable results under many different 
scenarios. As explained more fully in the Technical Supplement, OFHEO 
has evaluated its proposed models to ensure that they yield reasonable 
results under many different scenarios, use widely accepted techniques, 
and are otherwise appropriate for OFHEO's purposes.
    OFHEO is proposing statistical models for single family mortgages 
that were estimated using multinomial logit specifications for 
quarterly conditional probabilities of default and prepayment. The 
multifamily model was estimated similarly, although it is based upon 
annual, rather than quarterly, conditional probabilities of default and 
prepayment, as described more fully in the discussion of the 
multifamily default/prepayment issues, below. There are several 
advantages to using the multinomial logit specification. First, it 
guarantees that the estimated and projected probabilities of default 
and prepayment always lie between 0 and 100 percent. Second, one can 
estimate weights for the impact of specific explanatory variables on 
the probabilities of default and prepayment separately. Third, it is 
possible to specify different lists of explanatory variables for each 
type of event. Fourth, the model automatically accounts for the impact 
of differences in the estimated probability of default on prepayment 
and vice versa. Finally, estimation routines for multinomial logit 
models are readily available in a large number of commercially 
available statistical software packages.
e. Choice of Explanatory Variables for Default and Prepayment
    In the ANPR, OFHEO requested comment on the appropriate explanatory 
variables to use in statistical models of default and prepayment. OFHEO 
asked specifically about how to account for the effects of house 
prices, interest rates, and other economic factors, and whether to 
include measures of mortgage age and mortgage value as explanatory 
variables. OFHEO also asked about empirical and theoretical approaches 
to estimation of multifamily credit risk, and several respondents 
addressed the issue of explanatory variables in responding to that 
question.\92\ Because there are some differences between the 
explanatory variables for single family and multifamily models, the 
comments on explanatory variables are discussed separately for the two 
models. Some comments related to specific explanatory variables are 
discussed below in connection with the discussion of the particular 
variable.
---------------------------------------------------------------------------

    \92\ No commenters provided suggestions on how to actually model 
multifamily mortgage defaults and prepayments.
---------------------------------------------------------------------------

(i) Comments on Explanatory Variables for Single Family Modeling
    Freddie Mac suggested that using mortgage product, property type, 
occupancy status and current LTV as explanatory variables would explain 
a significant portion of the differences in default rates without 
venturing into more complex relationships that might prove unreliable 
for purposes of the stress test. Freddie Mac recommended caution in the 
consideration of mortgage age as an explanatory variable, noting that 
while age may be a valuable proxy for unmeasurable determinants of 
default, it should not take on such importance that mortgage age 
patterns dominate the capital requirements. In contrast, Freddie Mac 
did recommend that OFHEO include a measure of the mortgage premium 
value (reflected by the difference between the interest rate on a given 
mortgage and the current market interest rate for a similar loan) in

[[Page 18130]]

its modeling efforts, as an adjunct to borrower equity. Freddie Mac 
cited its own research showing that borrower default choices do respond 
to differences between the mortgage coupon rates and current market 
rates of interest.
    World Savings stated that OFHEO should be cautious about including 
unemployment rates as an explanatory variable in any statistical model 
of mortgage performance, because the statutory stress test takes a 
regional experience and uses it to imply a national recession. World 
Savings reasoned that, in a regional recession, homeowners who lose 
their jobs might find employment elsewhere but retain their homes. They 
may rent their homes until such time as house prices again rise enough 
to permit them to sell their properties without incurring a loss. 
However, in a national recession, such opportunities would not be 
available and the dynamics of default could be much different.
    MRAC recommended using the following variables: current LTV, length 
of residence, mortgage term and type, loan purpose, occupancy status, 
primary home status, relocation loan status, consumer credit 
information, and mortgage premium value. Recognizing that length of 
residence is not always available to researchers, MRAC suggested that 
mortgage age could be used instead. The MBA recommended including 
measures of borrower equity, mortgage premium value, and product type 
differences in a statistical model. Standard and Poor's asserted that 
mortgage age is a very important explanatory factor, noting that 80 
percent of all defaults occur by the seventh year of a mortgage pool.
    The VA asserted that borrower equity is the most important 
determinant of default and prepayment rates and recommended that OFHEO 
think of explanatory variables in two categories: those that indicate 
the borrower's ability to pay, and those that indicate the borrower's 
ability to sell the property. The former category could include such 
things as job loss, divorce, necessary relocation, and hazard loss 
(e.g., uninsured fire or water damage to the home). The latter category 
could include the borrower's equity position and ability to complete a 
property sale quickly. The VA also mentioned that its own statistical 
model of default and prepayment rates includes regional unemployment, 
house sale activity measures, and a house-purchase-affordability index.
    NAR recommended that OFHEO include a factor for mortgage age, but 
not for the mortgage premium value. While NAR accepted the theoretical 
justification for including mortgage value in a statistical model, it 
did not find its influence on defaults to be statistically significant 
in its own modeling efforts. NAR also mentioned a factor not discussed 
by other commenters--the relative size of each loan. NAR commented that 
the influence of house price appreciation on default depends on whether 
the loan has a high or low balance, and that OFHEO should carefully 
analyze this issue in the context of Enterprise experience. In addition 
to these comments, NAR also provided, without further explanation, a 
list of all the variables it believes should be included in a 
statistical model of default and prepayments. Listed were: origination 
LTV, ratio of the mortgage coupon rate to the current market rate for 
home mortgages, current LTV, loan size, presence of credit enhancement 
(e.g., private mortgage insurance), house price dispersion, transaction 
costs, the burden on household cash flow of servicing the mortgage, 
origination year of the mortgage, policy year (age) of the mortgage, 
mortgage premium value (for prepayment only), region of the country, 
unemployment rate, inflation, regional household mobility rate, 
mortgage product characteristics, and net borrower equity in the home.
(ii) Comments on Explanatory Variables for Multifamily Modeling
    OFHEO received fewer responses to its ANPR questions on approaches 
to multifamily modeling than it did to questions related to single 
family mortgage performance modeling. The import of these comments was 
to direct OFHEO to look at property cash flows as the primary influence 
on defaults. Freddie Mac emphasized that cash flow after mortgage debt 
service, as measured by the debt coverage ratio (DCR) is important, as 
are property equity and balloon terms. It also mentioned the need to 
measure multifamily market conditions directly, rather than relying 
upon single family house price appreciation to update explanatory 
variables over time. Freddie Mac further indicated that OFHEO needs to 
take into account significant factors that affected multifamily default 
rates during the 1980s, such as tax law changes, but should not include 
in the stress test the effect of any speculative political factors, 
such as potential legislative actions.
    Standard and Poor's also suggested that DCR should be the focal 
point for multifamily mortgage default risk, but added that the quality 
of the real estate securing mortgages is also considered in the S&P 
credit analysis. ACB recommended accounting for the changing cash flow 
position of the mortgaged property (i.e., using the DCR), rather than 
relying solely on net income, and including factors for tax laws and 
depreciation allowances. It also commented that, while data is not 
available to consider these additional variables, the underlying 
determinants of multifamily defaults are factors that lead to problems 
in tenant rental payments: unemployment, reduced hours of work, and 
reduced income. HUD suggested considering the corporate bankruptcy 
literature when deciding how to model multifamily defaults. This 
literature emphasizes changes in the cash flow position of multifamily 
properties. HUD also commented that OFHEO should treat balloon payoffs 
differently than normal, early prepayments.
(iii) General Approach
    Models of mortgage performance are models of borrower behavior--of 
individual borrowers' decisions whether to continue making monthly 
mortgage payments, to prepay, or to default. Each month, every borrower 
must choose among these three options. Because mortgage performance 
models are an attempt to predict how borrowers will choose to exercise 
these options, financial options theory provides the most widely 
accepted conceptual framework to link these borrower choices to 
differences in the underlying loan characteristics and economic 
conditions.\93\
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    \93\ This conceptual framework is the basis for nearly all 
mortgage performance research. It applies to all of the mortgage 
performance models referenced in the ANPR (See 60 FR 7470-7471, Feb. 
8, 1995, footnotes 11 and 13). Other references can be found in the 
Technical Supplement to this regulation. Financial options theory 
treats a mortgage like a bond issued by the borrower with embedded 
financial options to default or prepay, which borrowers will 
exercise when it is in their financial interest to do. From the 
lender or mortgage investor's perspective, this conceptual framework 
is sometimes referred to as ``contingent claim analysis.'' The 
mortgage investor, as bondholder, has a claim to a cash flow 
(mortgage payments), the value of which is contingent upon the value 
of the options to the borrower and the actions of the borrower with 
respect to the mortgage property (e.g., property maintenance). The 
choice to pay off (prepay) a mortgage is likened to a ``call'' 
option, where the borrower effectively buys back the mortgage from 
the lender at the book (face) value. The choice to default is seen 
as a ``put'' option, where the borrower sells the mortgage back to 
the lender at the current market value of the collateral property. 
The choice of an options-based model is consistent with the apparent 
underlying assumption of the preponderance of ANPR comments, which 
generally relate to how to account for factors that affect the 
exercise of these options.
---------------------------------------------------------------------------

    In the options theory framework, the most important variables are 
borrower equity and interest rates. When equity is

[[Page 18131]]

negative, that is, the property value is less than the outstanding 
mortgage balance, the default (put) option is said to be ``in the 
money.'' That term is used to mean that, theoretically, the borrower 
might find it financially advantageous to default in order to eliminate 
the negative equity position in the mortgage.\94\ When equity is 
negative, maintaining the mortgage through regular monthly payments 
leaves the borrower paying more for the property than it is worth. 
Under such conditions, default becomes an economically rational option 
for many borrowers, particularly those who may be undergoing other 
financial stresses, such as unemployment, divorce, health problems, 
etc.
---------------------------------------------------------------------------

    \94\ Negative equity is only one factor that influences the 
borrower's decision. Borrowers are usually personally liable on the 
note, which means that default could have numerous negative 
consequences beyond losing the property in foreclosure. For this 
reason, the model recognizes that negative equity does not cause a 
default, but simply makes it more likely.
---------------------------------------------------------------------------

    In an options-based model, interest rate changes create positive or 
negative value in the mortgage itself. This value is referred to in the 
ANPR as ``mortgage value.'' It is also sometimes referred to as the 
mortgage premium value. That is, the current mortgage has a ``premium'' 
or positive value to the borrower--it is worth holding on to--if the 
coupon interest rate is below current market rates. That mortgage value 
is reduced if current market rates are below the coupon rate. If a 
borrower is in a position of negative property equity due to declines 
in local house prices, but has a below market rate mortgage, the 
mortgage premium value reduces incentives to default. On the other 
hand, an above market rate mortgage could, in theory, increase the 
incentive to default for the same borrower.
    The mortgage premium value is inversely related to the value of the 
prepayment (call) option. When current market rates are below mortgage 
coupon, the call option is ``in the money,'' and its value is high. 
When the mortgage rate is below market, the call option is ``out of the 
money,'' and its value is low. Borrower equity also plays a part in 
prepayment determination; generally, it must be a certain positive 
amount before lenders will offer refinance opportunities. It must also 
meet a positive threshold before a property can be sold without the 
borrower incurring out-of-pocket expenses. However, as long as minimum 
equity thresholds are met, the higher the mortgage coupon rate is above 
the market rate, the greater is the incentive for a borrower to 
exercise the prepayment option by paying off the existing mortgage from 
the lender with the proceeds of a new loan.\95\
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    \95\ It is also possible that borrowers exercise the prepayment 
option with personal equity, liquidating other assets to pay off the 
mortgage even if property equity is negative. Borrowers may also 
turn to alternate lenders, who offer loans with LTVs higher than 
those usually purchased by the Enterprises, for refinancing 
opportunities when borrowers have little or no positive property 
equity.
---------------------------------------------------------------------------

    Although property equity and interest rates are the predominant 
variables of relevance in an options approach to mortgage termination 
modeling, many other factors affect borrower decisions to exercise a 
default or prepayment option.\96\ For single family mortgages, some of 
these factors are: (1) the potential for lender deficiency judgments, 
which reduce borrowers' ability to force lenders to absorb the negative 
property equity through defaulting; (2) borrowers' desire to maintain 
access to credit at preferential rates, which will also make them more 
hesitant to default; (3) moving costs, which reduce the value of the 
default option; (4) forced mobility due to job loss (or relocation) or 
family disruption, causing default or prepayment when it would not 
otherwise be financially advantageous to terminate the mortgage; (5) 
expected future mobility, which reduces tendencies to prepay in the 
present when that option is otherwise ``in the money''; and (6) the up-
front expenses involved in prepayment, which require that interest 
rates fall by a certain amount before it is really advantageous to 
prepay. For multifamily mortgages, the additional factors that affect 
the borrower's decision to exercise an option to default or prepay are: 
(1) property cash flow and the ability to service the mortgage; (2) the 
value of depreciation write-offs in reducing tax burdens; (3) 
prepayment penalties, which reduce the value of refinancing in the 
early years of a loan; and (4) balloon terms, which generally require a 
loan to be refinanced at maturity. Balloon term considerations are more 
important for multifamily than for single family mortgages because 
balloons are the predominant instrument type in the conventional, 
multifamily mortgage market.
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    \96\ Empirical studies have shown that mortgage borrowers are 
not ``ruthless'' in their exercise of these options. First, just 
being ``in the money'' at a point in time does not mean that an 
optimal ``strike price'' has been reached, where the option value is 
maximized. Second, there are many other factors that affect both 
option value and whether borrowers will default or prepay their 
mortgages.
---------------------------------------------------------------------------

    In choosing which variables to include in estimating the 
statistical models used in the stress test, OFHEO considered financial 
options theory, ANPR comments, data availability, the need for 
simplicity in model design, and the need to meet multiple statutory 
objectives while implementing a credit stress test based on the 
benchmark loss experience. In selecting explanatory variables to use in 
running the stress test, OFHEO considered whether they were necessary 
to reflect the differences in loan characteristics and interest rate 
environments as required by the 1992 Act. Some variables were used to 
estimate the statistical models, but they did not meet the criteria for 
inclusion in the stress test itself.\97\ They are represented by 
simplifying assumptions in the stress test so that their values do not 
vary across loans or time. All variables used to estimate the models 
and any other variables suggested by commenters are discussed below. 
The variables common to both single family and multifamily analysis are 
discussed first, followed by a discussion of variables unique to each.
---------------------------------------------------------------------------

    \97\ Any variable that is included as an explanatory variable in 
the stress test is also used to estimate the model.
---------------------------------------------------------------------------

(iv) Common Single and Multifamily Variables
(a) Measures of Borrower Equity
    The actual variable used in the proposed stress test to capture 
borrower equity positions is the probability of negative equity--the 
probability that the value of a mortgage will be larger than the value 
of the property securing it, so that the default (put) option is ``in 
the money.'' Calculation of this explanatory variable uses the measures 
of property value described in section III. A. 4. d., Property 
Valuation, along with original loan amortization schedules.\98\ 
Measuring the probability of negative equity is appropriate because the 
actual appreciation rates of individual properties are unknown and 
because such a measure gives the best representation of the percentage 
of loans in any given pool or portfolio that are at risk of default. 
The probability of negative equity is also included in prepayment 
equations, because negative equity may prevent prepayment by making it 
difficult to refinance. This variable, therefore, has opposite effects 
on default and prepayment rates. Increases in the probability of 
negative equity mean that fewer loans in the pool qualify for 
refinancing, which decreases prepayment rates. At the same time, 
borrowers who are forced to relocate or

[[Page 18132]]

who experience a loss of income may have difficulty prepaying, making 
the default option a more likely borrower strategy.
---------------------------------------------------------------------------

    \98\ In the estimation of single family default and prepayment 
equations, and in the stress test simulation of default and 
prepayment rates, balloon loans are amortized over their original 
rather than amortization terms. In the final rule OFHEO intends to 
substitute amortization term for original term in the calculations 
for balloon loans.
---------------------------------------------------------------------------

    For multifamily loans, the stress test uses a variable capturing 
the joint probability of negative equity and negative cash flow to 
predict default. As highlighted by the ANPR commenters, cash flow may 
be more important than equity for multifamily default. Although 
negative equity is a necessary condition for the default option to be 
``in the money,'' it is not a sufficient condition for default. Default 
will maximize wealth only if cash flows are also negative. When the 
equity is negative, but cash flows are positive, default is not 
rational because the borrower would give up positive income. Because 
both negative equity and negative cash flow are required for default to 
occur, the primary variable proposed to explain multifamily default is 
the joint probability that a property has both negative equity and 
negative cash flow.
    Additional consideration is given to the equity position of 
borrowers with balloon loans when those loans mature. At the balloon 
maturity point, when borrowers must pay off and find new financing, 
weak property financials can lead to even higher default rates than 
might occur earlier in the life of the loans. The multifamily model, 
therefore, gives additional weight to the joint probability variable in 
the balloon maturity year to reflect the increased risk that a borrower 
will not qualify for a new mortgage.\99\
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    \99\ OFHEO does not propose a similar treatment of single family 
balloon mortgages at this time, because they are not substantial 
portions of single family loan portfolios of the Enterprises, their 
balloon point refinance qualification standards are not as stringent 
as those for multifamily loans, and the Enterprises readily help 
single family borrowers to refinance balloon mortgages.
---------------------------------------------------------------------------

    Multifamily balloon loan payoff is also a function of the financial 
characteristics of the underlying property, because loans must meet 
equity and cash flow standards before new financing can be secured. To 
capture the impact of equity and cash flow on the ability of a borrower 
to refinance a multifamily loan at the balloon point, the stress test 
uses a variable that measures the joint probabilities that both 
property equity and cash flow are at sufficiently high levels to 
qualify for refinancing.
(b) Mortgage Premium Value
    OFHEO posed a question in the ANPR about use of the mortgage value 
(mortgage premium value)--the financial value of an above or below 
market rate mortgage coupon--as an explanatory variable in default 
equations. The mortgage premium value is a measure of the value of the 
prepayment option to the borrower, that is, the value of prepayment 
before accounting the transaction costs of prepayment. It is, 
therefore, an important variable used by all the models to explain 
prepayment behavior. At issue is whether this factor should also be 
used to help explain default behavior.
    ANPR commenters had differing views on this issue. Those suggesting 
that it should be used were Freddie Mac and VA. Two other commenters, 
NAR and ACB, were supportive in theory, but were not confident that a 
statistically valid relationship to default rates could be found, at 
least for single family mortgages. MRAC included the difference between 
the mortgage coupon rate and current market interest rates (a proxy for 
mortgage premium value) in its list of explanatory variables for a 
default/prepayment model. This is a proxy for the mortgage premium 
value.
    As explained earlier, options theory suggests that increases in the 
value of the prepayment option (resulting from lower interest rates) 
should increase both prepayment and default rates because the current 
mortgage becomes expensive compared to alternatives. Prepayments 
increase because refinancing becomes attractive. Default rates increase 
for borrowers who already have negative property equity because some 
such borrowers relieve themselves of both the negative property equity 
and the expensive mortgage by defaulting and then renting, or by taking 
out a new mortgage to purchase another property. Conversely, increases 
in market interest rates increase the value of holding on to an 
existing mortgage, and thus may decrease default rates as well as 
prepayments.
    While recognizing that there is a theoretical basis to include a 
mortgage premium value variable in the default equations, OFHEO 
proposes, nevertheless, to limit its use to prepayment equations. The 
influence of interest rate changes on mortgage defaults is captured 
adequately in single family default equations by a ``burnout'' 
variable, which measures the instances when borrowers have not taken 
advantage of previous refinancing opportunities. This variable is 
explained in a later discussion under section III.A.5.e., Choice of 
Explanatory Variables for Default and Prepayment. A burnout variable is 
not included in the multifamily equations, because prepayments are 
severely limited by prepayment restrictions.
    For prepayment equations, the actual variable used to capture the 
prepayment option value is a relative spread variable: the difference 
between the current mortgage coupon rate and the current market 
interest rate, as a percentage of the current mortgage coupon rate. 
This variable has been shown to provide an approximation of the 
mortgage premium value.\100\
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    \100\ This approximation of the mortgage premium value was 
introduced by Y. Deng, J. M. Quigley, and R. Van Order, (1996) 
``Mortgage Default And Low Downpayment Loans: The Costs Of Public 
Subsidy,'' Journal of Regional Science and Urban Economics 26(3-4), 
263-285.
---------------------------------------------------------------------------

    For multifamily mortgages, this relative spread variable is not 
included in the default equations, because the interest rate effect on 
default rates is reflected adequately in the joint probability 
variable. Declines in interest rates increase the present value of 
after-debt income stream generated by the property, and thus its market 
value, all else equal. Consequently, multifamily property values 
generally rise when interest rates fall.\101\ Thus, a relative spread 
variable is not included for multifamily defaults.
---------------------------------------------------------------------------

    \101\ While market interest rates do have some effect on prices 
of single family homes, the effect is not as direct as it is for 
multifamily and other investment properties.
---------------------------------------------------------------------------

(c) Mortgage Age
    OFHEO proposes to include mortgage age as an explanatory variable 
in its single family and multifamily models, as recommended in the ANPR 
comments. OFHEO found that conditional probabilities of default and 
prepayment of Enterprise loans exhibit characteristic age profiles that 
increase during the first years following origination, peak sometime 
between the fourth and seventh years, and decline thereafter.
    Because the benchmark loss experience was based entirely upon newly 
originated loans, an adjustment is necessary to account for the fact 
that at any point in time Enterprise single family portfolios consist 
of loans with varying ages. Adding mortgage age as an explanatory 
variable provides such an adjustment by allowing conditional default 
and prepayment probabilities to vary during the stress period in ways 
that historical profiles indicate are appropriate for loans of each 
age. Although Freddie Mac raised a concern that mortgage age might have 
too large an effect in the stress test, OFHEO research indicates that 
this is not the case. Although mortgage age is an important variable in 
the models, it does not diminish the impact of other, more

[[Page 18133]]

direct risk factors included in the stress test.\102\
---------------------------------------------------------------------------

    \102\ Mortgage age combines with the constant term in the 
statistical default and prepayment equations to create what can be 
called ``baseline'' rates of default and prepayment: the time series 
of rates that would occur if all other influences were absent. Once 
variables representing those other influences are added to the 
equations, the actual patterns of default and prepayment rates can 
vary greatly from the baseline paths.
---------------------------------------------------------------------------

(v) Additional Explanatory Variables Used in the Single Family Model
    The following discussion addresses additional explanatory variables 
that are used only in the single family model. A list of additional 
explanatory variables for the multifamily model is provided after this 
discussion of single family variables. The variables discussed below 
help to complete or modify the basic option valuation for single family 
mortgages. The original LTV ratio helps to account for differences in 
default and prepayment rates due to borrower financial status. 
Occupancy status accounts for differences between single family owner-
occupiers and investor-owners. Product-type factors adjust for 
differences that might be due to the unique risk characteristics of 
those products and the borrowers who use them. The yield curve slope 
accounts for different incentives to refinance between fixed-and 
adjustable-rate products. Some of the variables discussed below are 
used in statistical estimation of the models, but are represented by 
simplifying assumptions in the stress test.
(a) Original LTV Ratio
    Original LTV ratio is used in the stress test as a proxy for a 
number of factors related to the financial status of single family 
borrowers that are recognized widely as influencing the propensity of 
borrowers to default. Among these factors, which were mentioned by ANPR 
comments, are borrower income, net worth, and debt burdens. Information 
about these factors is not available for most of the loans in OFHEO's 
database. A variable that is available as a proxy for relative 
financial status of borrowers is the original LTV ratio.\103\ Both 
Freddie Mac and NAR recommended use of this variable. By making low 
down payments, high LTV borrowers signal that they are more likely to 
have few economic resources to finance the transaction costs of 
prepayment, or to endure spells of unemployment or other ``trigger'' 
events that might cause them to exercise their option to default. Also, 
high LTV borrowers demonstrate a willingness to ``leverage'' the 
financing of the home purchase, which may mean that they are more 
likely to exercise their default option when it is in the money. For 
these reasons, OFHEO found that original LTV is an important risk 
characteristic of mortgages, which OFHEO proposes to use both in 
estimating the single family model and in running the stress test.
---------------------------------------------------------------------------

    \103\ Although credit scores could be a good indicator of the 
financial status of borrowers, as discussed below under section III. 
A. 5. e. vi. f., Credit Scores, their usefulness for developing and 
implementing a default/prepayment model in the stress test is 
limited because credit scoring is a fairly recent development in the 
mortgage industry.
---------------------------------------------------------------------------

(b) Occupancy Status
    Historically, single family loans to owners who live in the 
collateral property have exhibited different performance than similar 
loans made to investors who rent the property. Difference in occupancy 
status is one of the loan characteristics that the 1992 Act 
specifically requires that OFHEO take into account in the stress test. 
It is also a distinction often made by the mortgage industry, because 
of a clear difference in the risks of borrower default or prepayment. 
Owner occupants are less likely than investors to exercise the default 
option because of the direct benefits occupants receive from the 
consumption of housing services. Also, owner occupants are more likely 
to prepay for non-financial reasons, such as residential mobility, than 
are investors.
    The statistical equations used in the stress test were estimated 
with an investor loan indicator variable that captures the differential 
default and prepayment risk of these mortgages. However, to capture the 
differential risk of investor loans in the proposed stress test, OFHEO 
makes a simplifying assumption that investor loans are spread equally 
across all loan groups, according to their percentage in the overall 
Enterprise book of business, rather than creating separate loan groups 
for investor mortgages. For example, if investor loans are four percent 
of all loans for a particular Enterprise in a particular starting 
quarter for the stress test, then four percent of the loans in each 
aggregated loan group are presumed to be investor loans for purposes of 
running the stress test. The statistically derived investor-loan 
weighting factor (statistical coefficient) in each default and 
prepayment equation is then applied to the four percent figure to 
arrive at the differential investor loan risk for every loan group. 
Because investor loans are a small percentage of Enterprise single 
family portfolios and are heavily concentrated in the 70 to 80 percent 
LTV category, OFHEO's simplifying approach has no significant impact on 
loss rates.\104\ The exact algorithms used in the proposed stress test 
to capture investor loan risk are detailed in section 3.5.2.3.2.5., 
Occupancy Status (OS), of the Regulation Appendix.
---------------------------------------------------------------------------

    \104\ Loans on owner-occupied properties in the Enterprise 
portfolios also have a central LTV range of 70-80 percent. Thus, 
attributing some investor loans to higher LTV categories and some to 
lower categories, by assuming they have the same overall LTV 
distribution as do owner-occupied loans, has offsetting effects on 
predicted credit risk.
---------------------------------------------------------------------------

(c) Product Type
    The 1992 Act expressly requires OFHEO to take differences in 
mortgage product type into account. In addition, because the benchmark 
loss experience was identified using the 30-year fixed-rate mortgage, 
it is necessary to reasonably relate the default experience of other 
types of mortgage products to the benchmark. Most commenters suggested 
some type of multiplier approach for other single family mortgage types 
that would measure the risk of these products in proportion to the risk 
of the benchmark loan type. OFHEO's proposed approach is broadly 
consistent with the thrust of these comments. Because comments received 
by OFHEO focused particularly on relating various mortgage product 
types to the benchmark experience, these comments are discussed later 
under section III.A.7.b., Relating Other Single Family Products to the 
Benchmark. This section discusses the way in which mortgage product 
type differences are handled in the single family mortgage performance 
model.
    The stress test uses two primary sets of statistically estimated 
single family default/prepayment equations, one for fixed-rate and one 
for adjustable-rate mortgages. A third set of equations, which may be 
thought of as modified fixed-rate equations, is used to project the 
performance of less prevalent single family mortgage types relative to 
the performance of 30-year FRMs. This final set of equations includes 
as explanatory variables unique product-type indicators for 15-year 
fixed-rate mortgages, 20-year fixed-rate mortgages, balloon mortgages, 
FHA/VA-insured mortgages, and second liens. Description of these 
specific product-type variables and their derivations are included in 
section 3.5.2.3.2.8., Product Type Adjustment Factors of the Regulation 
Appendix and section IV.B.5.j., Product Type Indicators, of the 
Technical Supplement. Product type indicators allow estimation of 
multiplier-like effects using all available historical data, and they 
assure that measured differences in product-type

[[Page 18134]]

risk are consistent with the stress test environment. All products with 
variable payments over time are included as adjustable-rate mortgages. 
Other non-standard mortgage types, such as reverse mortgages and bi-
weekly mortgages, are included with their fixed-rate counterparts with 
similar mortgage contract terms (length of mortgage in years).
    As explained in section III.A.7.b., Relating Other Single Family 
Products to the Benchmark, some commenters were justifiably concerned 
that applying several product type multiples to a single loan would 
have an inappropriate compounding effect on default rates. OFHEO 
addressed these concerns in two ways. First, the multipliers were 
estimated in a multivariate statistical analysis within the default and 
prepayment probability equations, rather than applying fixed 
multipliers to estimated default rates for 30-year fixed-rate loans. 
This approach provides adjustment factors that are most consistent with 
broad historical experience and with the other risk factors in the 
model. By controlling for other explanatory variables, only the 
residual effects of the differences in product type are captured by 
these product-type adjustment-factor multipliers, which limits the size 
of their effects. Second, the models include all other explanatory 
variables as categorical variables (indicators of value-range 
categories), instead of as continuous measures of variable values. 
Using categorical variables helps control for unreasonable compounding 
risks, by preventing the combination of low house-price growth and 
sustained adverse interest-rate movements in the stress test to cause 
default rates to rise to unrealistic levels. For example, the stress 
test gives the same default weight to all probability of negative 
equity values above 35 percent, which effectively caps the influence of 
this variable in the stress test.\105\
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    \105\ The number of loans in the historic sample used to 
estimate the statistical model of default and prepayment rates gets 
very small as the value of the probability of negative equity rises 
much above 35 percent. OFHEO therefore does not believe that there 
is valid information on default risk that could be gained by 
allowing for categories of probability of negative equity above, for 
example, 50 percent.
---------------------------------------------------------------------------

(d) Yield Curve Slope
    The slope of the Treasury yield curve is included as an explanatory 
variable in the prepayment equations. Both the choice between ARM and 
FRM loans and the timing of refinancing are influenced by expectations 
about future interest rates and differences in short-term and long-term 
borrowing rates associated with the slope of the Treasury yield curve. 
The slope of the Treasury yield curve is measured in the proposed 
stress test by the ratio of the ten-year CMT to the one-year CMT. A 
high value for the slope of the yield curve indicates that short-term 
rates are low relative to long-term rates. A high value, therefore, 
reduces the likelihood that ARM borrowers will refinance into fixed-
rate mortgages, and increases the likelihood that fixed-rate borrowers 
will refinance into ARMs to take advantage of the more attractive 
interest rates.
(e) Burnout
    For single family mortgages, the proposed stress test uses the 
variable burnout to capture the effect of the inability of borrowers to 
refinance their mortgages due to equity or other credit constraints. 
Burnout is the adverse selection that occurs when borrowers retain 
their mortgages during periods when there are clear financial benefits 
to refinancing. In this context, adverse selection is reflected in the 
lower average credit quality of mortgages remaining in a pool after a 
significant refinancing opportunity, compared to the overall quality of 
the mortgages in the original, larger pool. Adverse selection occurs 
because borrowers and properties with higher credit quality refinance 
in higher proportions than do those with lower credit quality. The 
remaining mortgages, therefore, will experience higher conditional 
default rates. Accounting for this change in the underlying quality of 
a mortgage pool is preferable to using only a prepayment-option-value 
variable in predicting defaults, principally because its effect 
continues unchanged over time. The burnout variable in the stress test 
indicates whether, over the previous eight quarters of mortgage life, 
there have been at least two quarters with significant refinance 
opportunities, as defined by a two percentage point difference between 
the mortgage coupon rate and the market interest rate on fixed-rate 
mortgages.
    For similar reasons, burnout is also included as an explanatory 
variable in single family prepayment equations, although its effect is 
in the opposite direction to that in the default equations. As 
discussed in the ANPR, burnout suggests that prepayment rates will be 
less responsive to interest rate changes after a pool of mortgages has 
already undergone a significant period of refinance opportunities.
(vi) Single Family Variables Not Used in Running the Stress Test
    Addressed below are several variables suggested by ANPR commenters 
that either are not used in the single family default/prepayment model, 
or were included in the statistical estimations but are represented by 
fixed or constant values when the stress test is run. In general, to 
estimate the model, OFHEO used variables that had significant 
independent effects on default and prepayment rates. However, OFHEO 
does not propose to use all of these variables in running the stress 
test. Some variables are not used in the stress test because they would 
diminish the role of the benchmark loss experience in determining 
stress test credit risk. Others were not needed to reflect statutory 
requirements to distinguish among loan types and characteristics, or 
between the effects of the up-rate and down-rate scenarios. Allowing 
such variables to vary in value in running the stress test would create 
credit-risk dimensions that are unnecessary and not contemplated by the 
statute.
(a) Relative Loan Size
    Relative loan size \106\ is the ratio of the original loan amount 
to the average-sized loan purchased by the Enterprises in the same 
State and in the same origination year. This variable was included when 
estimating the statistical model to isolate differences in the 
performance of loans of above and below average size, but is not used 
in the stress test.
---------------------------------------------------------------------------

    \106\ Relative loan size should be distinguished from the actual 
original and current dollar balances of the loans, which are 
included elsewhere in the stress test.
---------------------------------------------------------------------------

    As suggested by NAR, OFHEO explored the different default 
propensities of loans with high and low balances using Enterprise data. 
OFHEO's use of a relative loan size variable in the statistical 
estimations of the single family model demonstrated that relatively 
larger loans tend to have higher prepayment speeds, but differences in 
default rates by loan size were small and inconsistent. OFHEO 
interprets the faster prepayment speeds of relatively large loans as 
reflective of the higher dollar value of the prepayment option on these 
loans. Households with relatively large loans may also have higher 
overall debt burdens and be more responsive to opportunities to 
refinance debt so as to lower payment burdens.
    The stress test does not use relative loan size as a variable, 
because it is not needed to reflect statutorily required distinctions, 
and including it as a variable would have necessitated a sevenfold 
increase in the number of loan group records in the stress test. OFHEO 
believed that the benefit

[[Page 18135]]

derived did not justify the additional complication of the stress test 
that would result. As a result, all loans are put into the ``average'' 
size category for this variable when running the stress test.\107\
---------------------------------------------------------------------------

    \107\ This value is part of the fixed-factor terms reported in 
section 3.5.2.3.3., Combining Explanatory Variables and Weights of 
the Regulation Appendix for each default and prepayment equation. 
Relative loan size is discussed in section B.5.i., Relative Loan 
Size of the Technical Supplement.
---------------------------------------------------------------------------

(b) Season of the Year
    The season (quarter) of the calendar year was included when 
estimating the statistical model to account for the potential impact of 
weather, school schedules, and seasonal employment patterns on 
residential mobility and default and prepayment. In order to avoid 
seasonal variation in the quarterly risk-based capital requirements 
when the model is applied in the proposed stress test, an average of 
the season of the year effects is used. Because of the actual 
statistical technique used to estimate the equations, this average 
effect is obtained by excluding the season-of-year variable from the 
stress test default and prepayment equation.\108\
---------------------------------------------------------------------------

    \108\ Seasonal variation is discussed in section B.5.g., Season 
of the Year, of the Technical Supplement.
---------------------------------------------------------------------------

    Use of seasonal variation was mentioned by Freddie Mac as a 
weakness of the termination models used by investment banks to value 
mortgage backed security pools. OFHEO agrees with Freddie Mac that such 
seasonal variation would complicate the stress test, by creating 
quarterly volatility in loss rates, with no particular safety and 
soundness benefit.
(c) Origination Year
    Freddie Mac and NAR recommended including origination year as a 
variable. This approach would capture differences in the performance of 
specific mortgage origination cohorts due to excluded factors such as 
regional income growth and unemployment, or changes in mortgage 
underwriting standards over time. OFHEO considered using this variable 
but found that origination year is not an inherent risk factor, is not 
needed to reflect the types of distinction required by the 1992 Act, 
and is incompatible with the requirement to relate stress test losses 
to the benchmark loss experience. The last point is most important. The 
benchmark loss experience captures loans with the worst origination 
year and the worst credit risk profile. Assigning to loans originated 
in a given year a unique underlying credit profile, which may be 
different from the benchmark credit profile, would remove an important 
element of the link between stress test losses and the benchmark loss 
experience. In addition, varying inherent credit risk by loan 
origination year would require speculative assumptions about loan 
quality for more recent origination years for which no credit-risk 
track record has yet been established.
    By not including origination year as an explanatory variable, the 
statistical equations capture average origination-year profiles of 
default and prepayment. As discussed later under in section III.A.7., 
Relating Losses to the Benchmark Loss Experience, these profiles are 
adjusted further to reasonably relate starting loan portfolios to the 
benchmark loss experience. If the stress test were to allow for 
origination year differences when estimating the statistical equations, 
it would be necessary to assign the benchmark origination year effect 
to all loans in the stress test to preserve a reasonable relation to 
the benchmark loss experience. This approach would complicate the 
stress test without changing the results that are obtained using the 
proposed approach.
(d) Unemployment
    Unemployment rates were listed by some commenters as a possible 
explanatory variable. For numerous reasons, OFHEO does not propose to 
include unemployment as a variable either in running the stress test or 
in estimating the statistical model. OFHEO does not propose to include 
unemployment rates as an explanatory variable in the stress test, 
primarily because it is not a loan characteristic, but a macro-economic 
variable, and it is not one of the economic variables specified in the 
1992 Act. In any event, the effect of economic-condition variables not 
specified in the statute, such as unemployment, are captured in the 
stress test by relating the stress test to the actual benchmark loss 
experience, because the appropriate values are inherent in that 
experience. Thus, reasonably relating the stress test to the benchmark 
loss experience, as described in the next section, captures the 
strenuous economic conditions required by the 1992 Act without adding 
more economic variables. Minimizing the number of variables used to 
define economic conditions is responsive to the comments of both Fannie 
Mae and Freddie Mac, who argued against unnecessary complexity.
(e) Purchase vs. Refinance Loans
    MRAC suggested that OFHEO take loan purpose into account. OFHEO 
considered whether this distinction should be included as a variable, 
but has proposed a stress test that does not distinguish between loans 
made for the purpose of purchasing and loans made for the purpose of 
refinancing property. OFHEO has found insufficient basis to distinguish 
between the risks of loans for purchases and loans for refinancing. 
Furthermore, OFHEO prefers not to create capital incentives based on 
loan purpose, except as required by statute (e.g., the occupancy status 
distinction).
(f) Credit Scores
    OFHEO does not propose to follow the recommendation of MRAC to use 
mortgage borrower credit quality considerations as explanatory 
variables. OFHEO is aware that the mortgage industry is moving toward 
risk-based loan pricing based, in part, on mortgage credit scores that 
rely heavily on borrower credit ratings.\109\ OFHEO is studying the use 
of credit scores by the Enterprises, and the potential for impact on 
stress test credit losses, but does not believe that it is appropriate 
to consider these in the stress test or to use them to estimate the 
models. First, it would be difficult, if not impossible, to reasonably 
relate credit risk differences based upon credit scores to the 
benchmark loss experience, because credit-scoring data are not 
available for benchmark era loans.\110\ Second, the proposed stress 
test is designed to reasonably relate starting the performance of 
mortgage portfolios to the benchmark loss experience based upon loan 
characteristic differences referenced in the 1992 Act, which do not 
include measures of borrower creditworthiness.\111\
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    \109\ The most widely used measure of borrower creditworthiness 
is a composite score developed by Fair Isaac Corporation, commonly 
referred to as a ``FICO score.''
    \110\ Archives at the credit repositories only go back to the 
late 1980s, and, even there, records are not complete.
    \111\ The fact that OFHEO does not consider differences of 
credit risk by credit scores in the proposed stress test does not 
limit the ability of the Enterprises to to make use of credit 
scores. The Enterprises may further stratify the risk 
classifications used by OFHEO in the proposed stress test, for 
purposes of internal capital allocation and guarantee pricing. For 
example, after determining the required regulatory capital for a 
particular product class the Enterprises may, if they choose, 
allocate the required capital among purchases of that product 
according to borrower credit scores, for internal purposes. Thus, 
the dimensions on which the Enterprises choose to develop risk-based 
guarantee pricing are not limited by stress test risk 
classifications.

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[[Page 18136]]

(vii) Additional Multifamily Explanatory Variables
    Understanding the choice of explanatory variables for the 
multifamily default/prepayment model requires understanding the way in 
which default and prepayment equations are organized. The stress test 
uses two default equations, to distinguish between different 
multifamily lending programs, and five prepayment equations, to 
distinguish between different product types. The multifamily model 
allows these various default and prepayment equations to interact with 
each other to provide appropriate default and prepayment rate 
projections for all multifamily loans, throughout the stress period.
    One of the two default equations is for purchases of newly 
originated loans (cash purchases),\112\ and the other is for negotiated 
swaps of seasoned loan pools for mortgaged-backed securities 
(negotiated purchases). This separation allows the stress test to 
account for differences in loan quality across the two programs. The 
Enterprises may take lower quality loans and properties in their 
negotiated purchase programs than in the cash purchase programs, but 
require significant credit enhancements from the seller/servicers to 
compensate.
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    \112\ Cash-purchase programs may involve delivery of loans for 
cash or for mortgaged backed securities. They are called ``cash'' 
programs because they involve the purchase of individual loans under 
published underwriting guidelines and pricing.
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    The five prepayment equations used to accommodate product-type and 
product life-cycle differences allow the proposed stress test to 
account for the effects of loan characteristics, such as yield-
maintenance provisions,\113\ adjustable interest rates, and balloon 
terms. It is more important to capture the unique features of balloon 
mortgages in the multifamily business than it is in the single family 
business because balloons make up the majority of multifamily 
portfolios. The five prepayment equations are for: (1) All fixed-rate 
loans in the yield-maintenance period; (2) fully-amortizing fixed-rate 
loans after yield maintenance requirements; (3) fixed-rate balloon 
loans after the expiration of yield-maintenance requirements (but prior 
to maturity); (4) all ARM loans (prior to maturity for balloon ARMs); 
and (5) all balloon loans (with fixed or adjustable interest rates) at 
and after the maturity year.
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    \113\ A yield maintenance provision permits prepayment, but 
requires the borrower to pay penalties to compensate the lender or 
investor for lost interest until the yield maintenance period 
expires.
---------------------------------------------------------------------------

    To see how these prepayment equations work together, note, for 
example, that fixed-rate balloon loans have three relevant time 
periods: first is ``in-yield maintenance,'' the time when the yield 
maintenance terms apply; second is ``post yield maintenance,'' the 
period after the yield maintenance term expires and prior to loan 
maturity; and third is ``post-balloon,'' the period starting when the 
loan is due in full.\114\ For loans that extend to and beyond the 
balloon point,\115\ OFHEO proposes a separate prepayment equation, 
which is referred to as a ``payoff'' equation because it is no longer 
possible to ``prepay'' loans on or after the balloon date.
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    \114\ Balloon loans with adjustable interest rates (rather than 
fixed coupon rates) do not have yield maintenance terms, so they 
only have two relevant periods--pre- and post-balloon.
    \115\ After the balloon maturity date, the Enterprises may 
permit loan extension.
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(a) Explanatory Variables in the Two Multifamily Default Equations
    The two multifamily default equations are similar except in two 
respects. First, the equation for cash purchases makes adjustments for 
loans purchased in original multifamily programs to distinguish them 
from more recent programs. Second, the negotiated purchase loan 
equation has an adjustment factor for loan programs that obligate the 
seller to repurchase loans when they are delinquent for 90 days. These 
distinctions will be discussed in the context of each explanatory 
variable.
(1) Joint Probability of Negative Equity and Negative Cash Flow
    As with single family loans, one of the most important factors 
affecting multifamily loan default is borrower equity. When the value 
of the property is less than the value of the mortgage, the borrower, 
by defaulting, can effectively ``sell'' or ``put'' a mortgage back to a 
lender at the value of the underlying property. However, as recognized 
by the ANPR commenters, there is a second consideration for commercial 
properties (including multifamily properties)--cash flow from the 
property. Even though equity is zero or negative, the borrower does not 
have an economic incentive to default as long as cash flows are 
positive.
    The stress test includes a default option valuation variable that 
allows for consideration of the cash flow position of the property, 
while also considering the borrower's equity position. A value for this 
variable, referred to as the joint probability of negative equity and 
negative cash flow, is calculated for each loan in each observation 
period. It measures the potential value of ``putting'' the mortgage to 
the lender and investor through default, given that both equity and 
cash flow are important.\116\
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    \116\ The equity and cash flow positions of a property are 
positively correlated. The joint probability of negative equity and 
negative cash flow variable used in the proposed stress test 
captures this relationship.
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    As shown in section D. 4. a. i., Joint Probability of Negative 
Equity and Negative Cash Flow, of the Technical Supplement, the joint 
probability of negative equity and negative cash flow for a project is 
the probability of having both LTV greater than 1.00 and DCR less than 
1.00. The proposed stress test uses loan amortization schedules, rental 
inflation, vacancy rates, and interest rates to update LTV and DCR, 
which are then used to update the joint probability variable values.
(2) Original Versus Current Loan-Purchase Programs
    OFHEO faced the issue of what, if any, adjustment should be made in 
the model to distinguish between loans purchased under original cash-
purchase programs (purchased pre-1988 for Fannie Mae and pre-1992 for 
Freddie Mac) and current programs. As noted by Freddie Mac, the 
Enterprises computed both DCR and LTV differently for loans purchased 
under original programs than they compute those ratios today for 
current purchase programs. OFHEO recognizes that in the 1980s it was a 
common appraisal practice to adjust actual rents (and therefore net 
operating income) upward by an estimate of annual inflation and to use 
optimistic vacancy rate assumptions. This practice resulted in an 
overstatement of actual DCR and LTV values at the time of loan 
origination. Current practice does not allow for such inflation 
adjustments of projected rents, and factors minimum levels of 
anticipated vacancies into property valuation, even if the property is 
fully rented at the time of loan origination.
    In addition to the overstatement of net income, original 
multifamily cash-purchase programs at the Enterprises had other 
significant weaknesses perhaps because the Enterprises only began 
purchasing conventional multifamily loans in 1983 and did not have 
experience with the differences from single family lending. Even 
controlling for the overstatement of rents and for changes in tax laws 
in 1986 that depressed real estate values, these weaknesses led to 
extraordinarily high loss rates. OFHEO views these large losses, to a 
large extent, as nonrecurring startup costs attributable

[[Page 18137]]

to inefficiencies involved in learning a new business. For these 
reasons, OFHEO believes that the Enterprises' multifamily lending 
programs in the early and mid-1980s are so different from the current 
programs that it would be inappropriate to consider those early loans 
to be the same type of mortgage product as the multifamily loans that 
are made today.
    The stress test accounts for the difference in the older loan 
programs and the newer programs in two ways. First, the stress test 
adjusts the origination DCRs and LTVs of original cash purchase loans 
to remove the estimated annual inflation factors and restate those 
ratios as they would be calculated by the Enterprises in their current 
program purchases.\117\ Second, the stress test includes a variable in 
the default equation that distinguishes between original and current 
cash purchase programs. This variable results in higher levels of 
default on original cash purchase loans than on newer loans.
---------------------------------------------------------------------------

    \117\ OFHEO found that loans acquired in negotiated swap 
arrangements in the early and mid 1980s were highly seasoned and had 
low default rates. They therefore did not appear to include the 
inflation factor evident in cash purchases. Therefore, OFHEO does 
not adjust DCRs and LTVs for loans in negotiated purchase pools.
---------------------------------------------------------------------------

    A significant consideration in OFHEO's proposal to distinguish the 
original cash purchase loans from loans purchased under current 
programs was that failing to make that distinction would create a 
relatively more severe (and far less) loss experience for multifamily 
loans than the benchmark loss experience creates for single family 
loans.\118\ In OFHEO's view, imposition of such extreme levels of 
default upon the Enterprises' multifamily loans would be contrary to 
the intent of the 1992 Act that rates of default and severity be 
``reasonably related'' to the benchmark loss experience. It is also 
possible that basing stress test losses on average default rates of 
original cash-purchase loans would result in an implied marginal 
capital requirement so high as to create an inappropriate disincentive 
to engage in new multifamily lending.
---------------------------------------------------------------------------

    \118\ The relationship of multifamily default rates to the 
benchmark experience is discussed later in section III. A. 7. c., 
Relating Multifamily Mortgage Performance to the Benchmark.
---------------------------------------------------------------------------

(3) Depreciation Write-offs and Tax Law Changes
    In the absence of a price index for multifamily properties, the 
stress test captures most of the changes in property value by updating 
DCR and LTV according to changes in rents, vacancies, and interest 
rates. However, changes in DCR and LTV that are due to other factors 
are not captured in these procedures. The most important missing factor 
is the tax benefit afforded to owners of investment real estate through 
depreciation write-offs. ACB commented that depreciation allowances 
have important effects on property cash flows. OFHEO recognizes this 
fact and that the allowances also have important effects on capital 
gains at the time of property sale. The tax value of depreciation 
write-offs significantly influences the return from multifamily 
property investments and, consequently, the default risk of multifamily 
mortgages.
    OFHEO agrees with Freddie Mac that tax law changes affecting 
multifamily default rates during the 1980's should be taken into 
account, but that OFHEO should not speculate on the effect of potential 
legislative or other governmental actions during the stress period. The 
proposed stress test incorporates an index that measures the value of 
depreciation write-offs for a new investor. It measures changes in 
quality due to changes in write-offs and allows OFHEO to reflect the 
effects of such changes on mortgage defaults historically. The actual 
index value used in the stress test is an approximation of expected 
values throughout the stress period.\119\ It is calculated based on 
depreciation rules and tax rates as they existed in 1997, with no 
adjustments for movements in interest rates since that time, or for the 
interest-rate shocks that will occur in the stress test. The tax rules 
governing depreciation allowances have the largest impact on the value 
of this variable. These rules changed significantly in 1986, but have 
not changed significantly since. Because the historical database 
included many loans originated before the tax rule change, OFHEO 
allowed the value of this explanatory variable to vary for purposes of 
estimating the statistical equations for multifamily mortgage default. 
However, due to the subsequent stability in those rules, OFHEO proposes 
to hold the value of this variable constant throughout the stress test. 
If the applicable tax rules change in the future, or if OFHEO believes 
that there are other reasons for either changing the specified value 
for the stress test or allowing its value to change throughout the 
stress test, OFHEO will initiate a new rule making process. However, as 
recommended by Freddie Mac in its ANPR comments, OFHEO will not 
speculate about tax law changes that might occur during the stress 
period. Due to data restrictions, the depreciation-allowance is only 
included in the cash-purchase default equation.\120\
---------------------------------------------------------------------------

    \119\ The stress test does not capture actual depreciation 
allowances for borrowers. Enterprise databases do not include the 
year of property purchase. Therefore, the exact depreciation rules 
affecting cash flows and investment value to existing owners are 
unknown. Even on newly constructed projects, the Enterprises 
generally do not purchase the mortgage until target occupancy rates 
are met, which may be some time after origination. For these 
reasons, it would be extremely difficult to determine the actual 
value of depreciation write-offs to current owners. Although the 
value to current owners affects the owner's cash flow, the value to 
potential purchasers (which would be based upon current appreciation 
rules) affects property value and the owner's equity in the 
property. Therefore, this explanatory variable for depreciation 
write-offs helps to reflect more accurately the true LTV of the 
mortgage.
    \120\ See section D. 4. a. ii., Construction of the JPt Variable 
of the Technical Supplement for details.
---------------------------------------------------------------------------

(4) Loan Programs with Seller/Servicer Repurchase Features
    Some Enterprise multifamily loan programs require seller/servicer 
repurchases of loans that become 90-days delinquent. For these programs 
a 90-day delinquency event is effectively a default, while for all 
other loans, default means a property loss event (short sale, note 
sale, third-party sale or foreclosure). To account for this difference 
when estimating the statistical model, OFHEO applied, as an explanatory 
variable, the ratio of 90-day delinquencies to full defaults. This 
treatment is important because the rate of 90-day delinquency events is 
always higher than the default rate for property loss events, and the 
loss severity for 90-day delinquencies is lower. By including this 
ratio, and thus including loans with the 90-day delinquency 
terminations, OFHEO was able to estimate a negotiated-purchase default 
equation based on a much larger data set than would have been possible 
otherwise.
(5) Balloon and ARM Payment Shock Risk
    Following HUD's suggestion, OFHEO analyzed defaults of Enterprise 
balloon loans at the balloon point. As a result, OFHEO proposes to give 
additional weight to the joint probability of negative equity and 
negative cash flow variable for balloon loans that survive to the year 
of balloon maturity. This extra weighting takes into account the 
increased risk that mortgages with weak financials will default as the 
balloon point approaches. Also, interest rate movements may create 
payment shock (change in the periodic mortgage payment) in the post-
balloon period, which affects the probability of default. The stress 
test accounts for the effect of

[[Page 18138]]

this shock directly through adjustments to effective DCR in the post-
balloon period. These adjustments then affect the joint probability of 
negative equity and negative cash flow, reflecting the fact that the 
decision to default or payoff is no longer a function of the original 
mortgage coupon rate, but of the prevailing market rates at the time of 
balloon expiration. In sum, the stress test reflects that the value of 
the default (``put'') option, as measured through the joint probability 
variable, becomes more significant for default rates in the post-
balloon period because there is increased pressure on the borrower to 
either default or refinance the property.
    ARMs also experience payment shock because of changes in market 
interest rates. ARM payment shock occurs periodically during the term 
of the loan, and ARMs continue to amortize after the payment shock, 
according to the original contract term. The ARM prepayment equation in 
the stress test accounts for these periodic changes in interest rates. 
In contrast, the payment shock for a fixed-rate balloon loan does not 
occur until the balloon point. Some loans in Enterprise portfolios are 
ARMs with a balloon maturity. These loans have payment shock every year 
and also at maturity. The proposed stress test models the annual 
changes in their DCRs resulting from changes in mortgage coupon rates 
and then adds an additional balloon shock through the additional weight 
given to the joint probability variable in the post-balloon period.
(6) Loan Size
    The stress test does not include a variable for loan size. S&P 
explained that it bifurcates commercial loan pools into two parts to 
calculate credit loss potential--the largest loan, and all other loans 
in the pool. S&P assumes 100 percent risk of default on the largest 
loan and average risk of default on the other loans. This approach is 
designed to recognize the uneven dollar credit loss risk inherent in 
pools that contain loans that are large relative to the total size of 
the pool. Credit risk for the pool is then estimated by S&P to be the 
sum of estimated credit risk on each part. S&P did not specifically 
recommend that OFHEO adopt this approach in the stress test.
    OFHEO agrees that S&P's methodology is appropriate for analyzing 
differential impact of large and small loans on potential credit losses 
in mortgage security pools. However, no one multifamily loan default 
could have a significant impact on total losses or capital for either 
Enterprise. For that reason, OFHEO decided not to propose any measure 
of loan size as an explanatory variable in the multifamily default/
prepayment model.
(b) Explanatory Variables in the Five Multifamily Prepayment Equations
    As explained above, the multifamily model uses five loan prepayment 
equations to identify unique product type and life-cycle 
characteristics. This approach is consistent with Freddie Mac's and 
MRAC's comments on accounting for mortgage product types and terms in 
the default and prepayment models. There are some differences in 
explanatory variables across these five equations, which are discussed 
below.
(1) Prepayment Option Value
    As discussed earlier, OFHEO proposes to use the relative interest 
rate spread to measure the prepayment option value (mortgage premium 
value) for prepayments. The relative spread is the ratio of the 
difference between the coupon rate and the current market interest rate 
to the coupon rate. To account for the asymmetry of effects from 
increases and decreases in interest rates, the spread is split into two 
variables.\121\ One is active if current market interest rates are 
above the mortgage coupon rate, and the other is active if current 
market rates are below the mortgage coupon rate. Decreased interest 
rates increase refinancing speeds. Increased interest rates decrease 
both normal refinancings and cash-out refinancings. Cash-out 
refinancings are refinancings in excess of the outstanding 
indebtedness. They are used to achieve a desired debt-to-equity ratio 
in the property as explained below in the discussion of current LTV. 
Relative spread variables appear in all prepayment equations except for 
the balloon and post-balloon payoff equations. At balloon maturity, all 
spreads become irrelevant, because borrowers are contractually 
obligated to pay off or refinance the property.
---------------------------------------------------------------------------

    \121\ Such explicit bifurcation is not required for the single 
family prepayment equations because the categorical nature of the 
spread variable used there allows for asymmetric effects.
---------------------------------------------------------------------------

    For the ARM prepayment equation, the relative spread variable is 
calculated by comparing the coupon rate to the current market rate on 
fixed-rate loans, rather than to the market rate for ARMs. This 
approach accounts for any incentive to refinance into a fixed-rate 
loan. Because there are no yield-maintenance terms or special 
incentives to refinance ARM loans when interest rates fall, the stress 
test includes one spread variable that captures both increases and 
decreases in interest rates. In addition, the stress test does not 
distinguish between life-cycle periods for ARMs; just one prepayment 
equation is estimated.
(2) Current LTV
    Another important issue in modeling multifamily loans is the 
propensity of investors in multifamily properties to refinance 
mortgages over time to increase their debt (leverage) ratios, and thus 
increase returns on invested equity.\122\ To capture the borrowers' 
ability to qualify for a new loan and the incentive to adjust debt-to-
equity ratio, the proposed stress test includes current LTV as an 
additional explanatory variable. If the current LTV falls, investors 
have more incentive to prepay and are more likely to find a lender 
willing to refinance the property.
---------------------------------------------------------------------------

    \122\ See Jesse M. Abraham and H. Scott Theobald, ``Commercial 
Mortgage Prepayments,'' in Frank Fabozzi and David Jacob, The 
Handbook of Commercial Mortgage-Backed Securities, New Hope, PA: 
Frank J. Fabozzi Associates, 55-74 (1997).
---------------------------------------------------------------------------

(3) Prepayment Option Value in the Yield-Maintenance Period
    During the yield-maintenance period, borrowers may prepay, but they 
must continue to provide the contractual yield until the yield-
maintenance period expires. Thus, a prepayment in the yield-maintenance 
period can be expensive, particularly in the early years of a mortgage. 
The more years to go in the yield-maintenance period, the greater the 
fee.\123\ To capture the declining financial cost of prepayment 
throughout the yield-maintenance period, OFHEO proposes a variable 
measuring years remaining until the end of the yield-maintenance 
period. This variable appears in the prepayment equation for fixed-rate 
loans in the yield-maintenance period.\124\
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    \123\ Because this effect runs counter to the effect of the call 
option value, OFHEO researched the possibility of a joint effect of 
the years-to-go and the rate drop variables. The fixed effects of 
the years-to-go variable proved to be a better predictor of actual, 
historical prepayments during yield maintenance periods.
    \124\ For loans with true prepayment prohibitions, or ``lock-
outs,'' the variable is set equal to the maximum number of lockout 
years throughout the lockout period. See section 3.5.4.3, 
Procedures, of the proposed Appendix to 12 CFR part 1750, subpart B 
for details.
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(4) Prepayment Option Value in the Pre-Balloon Period
    During the pre-balloon period, borrowers are uncertain about the 
level of market interest rates at the future balloon point. Hence, 
borrowers may be willing to pay in order to lock into a favorable 
interest rate, rather than take

[[Page 18139]]

their chances with possible adverse interest rate movements. This risk 
aversity with respect to interest rate movements prior to the time of 
balloon maturity gives rise to an additional financial value from early 
prepayment. OFHEO proposes two explanatory variables to capture the 
effect of risk aversity on prepayment rates in the pre-balloon period. 
They measure the additional effects of the primary prepayment option 
variable-relative spread-when it is in the money (market interest rates 
are lower than the mortgage coupon rate).
    The first variable provides an additional effect for interest rate 
drops in the year immediately prior to the balloon year, and the second 
provides for a separate, additional effect for interest rate drops in 
the second year prior to the balloon year. These two variables allow 
for increased incentives to refinance if the prepayment option is in 
the money in the period leading up to balloon expiration. They capture 
the risk aversity of borrowers with respect to future interest rate 
changes as balloon maturity approaches.
(5) Balloon and Post-Balloon Payoffs
    HUD commented that OFHEO should model the value of the refinancing 
option at the balloon point on balloon mortgages because the lender 
often has a contractual obligation to refinance at the borrower's 
option. OFHEO agrees that payoffs at the balloon point are different 
from prepayments before the maturity date, but has found that the 
lender generally does not have an unconditional contractual obligation 
to provide new funding if the borrower requests it. Payoff of the 
balloon loan (generally by new borrowing to refinance the property) is 
contractually required at term. If the borrower is successful at 
finding new financing at that point, the event that appears in 
Enterprise records is a payoff of the original loan and not a 
prepayment. Despite the contractual requirement of balloon payoff, not 
all loans terminate at the balloon point.\125\ Generally, balloon loans 
are extended beyond the maturity date because, although the property 
has weak financials, lenders are unwilling to initiate foreclosure on 
loans that have been making payments at the original coupon rate. To 
capture the ability of multifamily borrowers to obtain new loans at 
balloon expiration, and, therefore, to pay off the original mortgage, 
the model includes a variable similar to the joint probability variable 
used in the default equations--the joint probability that current DCR 
and LTV values are sufficient to qualify for a new mortgage. This is 
the only variable used in the pay-off equation for balloon mortgages, 
and it is based on minimum qualification criteria for multifamily 
mortgages, LTV  0.80 and DCR  1.20.
---------------------------------------------------------------------------

    \125\ See Elmer and Haidorfer, ``Prepayments of Multifamily 
Mortgage-Backed Securities,'' The Journal of Fixed Income, March 
1997, 50-63 (pointing out that not all loans terminate at balloon 
point); Abraham and Theobald, op. cit. (referring to this phenomenon 
as extension risk). OFHEO confirms the existence of post-balloon 
loans in Enterprise portfolios.
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(6) Effect of Fixed-Rate Loan Interest Rates on ARM Prepayments
    A final variable included in the ARM prepayment equation is the 
market rate on fixed-rate loans. This variable accounts for incentives 
to refinance ARM loans into fixed-rate loans to avoid future 
uncertainty regarding interest rate movements. If the FRM rate is high, 
borrowers expect interest rates to drop in the future and are likely to 
delay prepayment of ARMs. Likewise, when interest rates are low--
regardless of the spread between FRM and ARM rates--there is an 
incentive to refinance into a fixed-rate product to avoid potential 
increases in future interest rates.
6. Loss Severity
    Loss severity is the net cost to an Enterprise of a loan default. 
The three major cost categories are loss of loan principal transaction 
costs at both foreclosure and disposition, and asset funding costs 
throughout the process. The net cost is determined by crediting against 
these costs the revenues associated with the defaulted loan. The major 
revenues are proceeds from the property sale and from mortgage 
insurance or other forms of credit enhancement.
    In determining how to model loss severity in the stress test, OFHEO 
considered the following issues:
    1. what general approach to take in modeling loss severity,
    2. whether the stress test should model individual cost and revenue 
elements of loss severity or model severity as one single measure,
    3. what explanatory variables should be included explicitly in 
modeling loss severity, and
    4. an appropriate house price index for real estate owned (REO) 
properties.\126\
---------------------------------------------------------------------------

    \126\ REO properties are properties acquired as a result of 
foreclosure or similar action.
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a. General Approach to Modeling Loss Severity
    In the ANPR, OFHEO discussed four general approaches to estimating 
the separate effects of explanatory variables on loss severity. One 
approach is to use a multivariate statistical model to estimate the 
separate effects of explanatory variables on total loss severity rates. 
A second approach is to use statistical models relating the individual 
elements of loss severity to explanatory variables. A third approach 
would set fixed parameters for the elements of loss severity 
(foreclosure costs, carrying costs, and sales prices), while allowing 
final loss severity rates to vary based on other factors such as the 
presence of private mortgage insurance. A fourth, relatively simple 
approach would be to assume that all defaulted loans face a fixed and 
equal level of loss severity.
(i) ANPR Comments
    ACB and MRAC encouraged OFHEO to use a multivariate statistical 
model of loss severity. ACB, apparently assuming the stress test would 
include a statistical model of defaults, stated that ``[i]t is not a 
rational allocation of resources to develop a sophisticated model of 
mortgage defaults and then to apply a rule-of-thumb percentage to the 
unpaid principal balances.'' S&P described its use of data from the 
Great Depression as the basis for stress tests it uses to rate single-
family mortgage pools. Freddie Mac recommended that OFHEO use average 
loss severity rates from the benchmark loss experience, adjust them to 
account for the stress test interest rate environment, and apply 
additional adjustments for various property types.
(ii) OFHEO's Response
    OFHEO believes that a statistical model is the best approach to 
take into account loan seasoning and the dynamic nature of economic 
changes in the stress period. OFHEO agrees with ACB that it would be 
inappropriate to develop a sophisticated default model and then to 
apply a rule-of-thumb percentage to the UPB to determine loss severity. 
At the same time, OFHEO recognizes that developing statistical models 
of each loss element is unnecessarily complex. Based on its analysis of 
the available information, OFHEO proposes a two-part model for single 
family loss severity: a statistical equation for loss of loan principal 
and fixed parameters for the other cost elements. Specifically, the 
statistical model developed by OFHEO estimates loss of loan principal 
as a function of loan seasoning-updating the original LTV using HPI 
growth rates and loan amortization. For multifamily loss severity, 
OFHEO proposes to use only fixed cost element values. The rationale for 
this is explained below under section III. A.7., Relating Losses to the 
Benchmark Loss Experience.

[[Page 18140]]

    The approach outlined by S&P would not be appropriate for OFHEO's 
stress test because it does not adjust for loan seasoning or provide 
for a reasonable relationship to the benchmark as required by the 1992 
Act. However, consistent with the S&P approach, the stress test does 
provide for a greater than average drop in house prices for foreclosed 
properties. As discussed below, under section III. A.6. b., Elements of 
Loss Severity Modeled, the stress test uses a statistical equation to 
model the expected decline in values on foreclosed properties, which 
will be greater than the decline in property value associated with HPI 
assumptions used in the stress test. In addition, as discussed later 
under section III. A.7., Relating Losses to the Benchmark Loss 
Experience, the stress test adds an extra loss factor to relate stress 
test property value loss to the actual experience of the four-State 
benchmark.
    OFHEO agrees that Freddie Mac's recommended approach is simpler 
than using a statistical model. However, an empirically based 
statistical model is more versatile and flexible, allowing the stress 
test to reflect loss severity rates appropriate for each Enterprise's 
mix of loans and the stress test interest rate environment. OFHEO 
proposes a hybrid approach that retains the simplicity of fixed cost 
factors for most severity elements, while developing a more sensitive 
measure of property value, the element most affected by pre-stress test 
loan seasoning.
    OFHEO does not propose at this time to take property type 
differences into account in stress test loss severity rates, as 
suggested by Freddie Mac. Although OFHEO finds higher loss severity 
rates for investor-owned properties, accounting for this effect would 
increase significantly the number of loan group records used for 
starting books of business in the stress test. Given the small 
percentage of Enterprise portfolios that investor-owned loans comprise, 
OFHEO felt that the added complexity was not justified by the benefits 
of calculating severity rates for owner-occupied and investor-owned 
single family loans separately. Therefore, OFHEO does not propose to 
apply risk multiples for investor-owned properties in determining loss 
severities. Rather, the single set of cost elements used in the stress 
test are determined by Enterprise experience with all single family 
property types combined.
b. Elements of Loss Severity Modeled
    In addition to asking whether OFHEO should use a statistical model 
of loss severity, the ANPR asked whether the stress test should model 
loss severity as a single value or model the various cost and revenue 
elements of severity separately.
    All ANPR commenters favored, at varying levels, an element-by-
element analysis. The VA recommended that the stress test model the 
amount and timing of both the cost and the revenue elements of loss 
severity to provide more accurate estimates of Enterprise cash flows. 
HUD recommended that the loss severity model include certain individual 
cost elements, all of which would be valued separately by the proposed 
severity module. NAR stated that ``the modeling of loan loss severity 
should only include those factors that are independent of incidence of 
default'' and emphasized the importance of modeling time in default 
separately. In contrast, Freddie Mac stated that defaults and severity 
are products of the same underlying characteristics and economic 
factors. Freddie Mac suggested that stress test severity calculations 
differentiate loans by original LTV and coupon class and by product 
type distinctions. In addition, Freddie Mac favored using the rate of 
loss of principal balance from the benchmark loss experience.
    ACB supported using a sophisticated model of loss severity, which 
would, presumably, require breaking down severity into its constituent 
parts for analysis and modeling. MRAC suggested separate analysis of 
the elements of loss severity, including the estimated sale proceeds, 
holding time, monthly holding costs, and costs of sale.
    OFHEO agrees with the commenters that the stress test should model 
individual cost and revenue elements separately, rather than model them 
together as a single cost category. Such an approach allows the stress 
test to model the interrelationship of those elements that 
significantly effect loss severity. Accordingly, OFHEO proposes to 
model elements in three principal groupings: (1) loss of loan principal 
balance, (2) transaction costs (e.g., expenses related to foreclosure, 
and property holding and disposition expenses), and (3) funding costs 
on non-earning assets. OFHEO believes that measuring elements in these 
groupings is necessary to accommodate differences in the timing of 
various elements of loss severity and differences in the pre-stress 
test seasoning of loans. Each cost or revenue factor is applied at one 
of the following three points in time (each in terms of months from 
date-of-default): time of loan repurchase (for loans in security pools) 
or bad-debt write off (for retained loans); time of foreclosure 
completion; and time of foreclosed property disposition.
    In addition, consistent with Freddie Mac's comment, OFHEO's 
proposed loss severity calculations differentiate by LTV and coupon 
class. They also include product distinctions where those distinctions 
involve FHA/VA insurance, interest rates and amortization terms. The 
amount of the loss of loan principal balance is sensitive to loan 
amortization. Because 15-year mortgages amortize relatively early and 
more quickly, their predicted losses are much less than those on 
otherwise comparable 30-year mortgages.
(i) Loss of Principal Balance
    A critical element of loss severity is loss of loan principal 
balance, i.e., the difference between the outstanding principal balance 
on the loan at the time of default and the sale price of the foreclosed 
property. This loss occurs because of general declines in local housing 
values, the depreciation of the individual property, and/or discounts 
required to sell properties with ``foreclosure'' labels. To calculate 
this loss, the stress test uses a statistical model of the historical 
relationship between actual loss of principal balance on loans that 
have defaulted and the loss of principal balance predicted solely by 
calculating amortization on the loan and updating the property values 
with the HPI. Sale proceeds are then calculated as UPB minus the 
estimated loss of principal balance. Proceeds vary with differences in 
house-price appreciation and loan terms.
(ii) Transaction Costs
    The stress test includes two transaction cost elements in loss 
severity calculations: foreclosure/legal expenses, and property holding 
and disposition costs.\127\ Property holding and disposition costs are 
combined in the proposed stress test because they are both expensed at 
the time of property disposition. OFHEO proposes to use averages of 
these cost elements--in percent of outstanding principal balance--from 
all Enterprise experience with foreclosure and REO properties.
---------------------------------------------------------------------------

    \127\ Legal expenses are dominated by foreclosure costs, but 
they also include costs associated with gaining releases from 
borrower bankruptcy stays and property evictions.
---------------------------------------------------------------------------

    OFHEO did not follow Freddie Mac's recommendation to use all cost 
elements directly from the benchmark loss experience for transaction 
costs, because the stress test is national in scope. Therefore, it is 
appropriate to have a national blend of institutional factors such as 
foreclosure costs, property management fees, and sales

[[Page 18141]]

expenses, rather than the four-State blend from the benchmark 
experience.
(iii) Funding Costs
    Funding costs are considered an element of loss severity because 
the Enterprises must fund non-earning assets: first the defaulted 
loans, and then the REO properties. In its ANPR comments, Freddie Mac 
suggested that funding costs should be measured at the mortgage 
interest rate for the period from date of default to foreclosure 
completion. OFHEO agrees that the stress test should model funding 
costs. However, Freddie Mac's recommended approach ignores funding 
costs during the REO time period and would provide inaccurate measures 
of funding costs during the delinquency/default period. In the down-
rate scenario of the stress test, using the mortgage coupon rate for 
funding costs would overstate funding costs, while in the up-rate 
scenario it would understate funding costs.
    With one exception, the stress test measures asset funding costs 
through present-value discounting techniques, rather than computing 
explicit interest charges. Therefore, all severity elements are 
discounted by a cost-of-funds rate to produce the present value of each 
element in the month of default, regardless of when it may occur after 
that date. Cash flow discounting provides a consistent method of 
accounting for all timing issues involving cash flows from mortgage 
default to property disposition.
    The one exception to the rule of calculating funding costs through 
present-value discounting techniques is the explicit cost of covering 
interest passed through to investors in securitized loans (mortgage-
backed securities). These passthroughs occur for the first four months 
of loan delinquency, during which time the stress test uses the 
passthrough rate (the interest rate paid to holders of the securities) 
to calculate the asset funding cost. After the fourth month, when the 
loans have been repurchased from security pools and placed in 
Enterprise retained portfolios, the stress test treats these defaults 
identically to defaults in retained portfolios.
(iv) Factors Not Modeled
    ANPR commenters suggested several explanatory factors that are not 
included in the proposed single family loss severity model. These 
include distinctions based on State foreclosure laws, household 
liquidity, and the presence of private mortgage insurance.\128\
---------------------------------------------------------------------------

    \128\ Although private mortgage insurance is not an explanatory 
variable, proceeds from such insurance are accounted for in the 
severity calculation.
---------------------------------------------------------------------------

(a) State Foreclosure Law Differences
    Freddie Mac suggested that OFHEO not make State-level distinctions 
in loss severity calculations, explaining that attributing 
``differences in loss rates by states would approach undue intrusion 
and inappropriate micromanagement of the Enterprises.'' In contrast, 
NAR recommended that OFHEO make State distinctions.
    Although foreclosure time-frames and costs may vary based on State 
law and practice, OFHEO agrees with Freddie Mac that it would be 
inappropriate to model State-level differences. First, these 
differences do not represent loan characteristics, and, therefore, 
under OFHEO's approach to selecting variables to apply in the stress 
test, they are not appropriate. Second, if OFHEO were to allow for 
State-level differences in credit costs, the stress test would, 
essentially, be establishing State-specific capital requirements based 
upon nuances of State law. OFHEO would need to monitor developments in 
the many different State laws over time to adjust the parameters of the 
stress test. Third, the fact that the stress test uses loan data 
aggregated at the Census division level means that much of the 
variability in foreclosure costs observed at the State level 
disappears.
(b) Independence of Loss Severity Rates From Default Rates
    Freddie Mac commented that default and loss severity are products 
of the same underlying factors, most particularly original LTV and 
property value appreciation over the life of the mortgage. NAR 
recommended that the loss severity model ``only include those factors 
that are independent of the incidence of default.'' OFHEO agrees with 
Freddie Mac on this point, because OFHEO's research indicates that loan 
seasoning has an important impact upon severity rates that is 
independent of its impact on defaults. The use of loan seasoning in the 
stress test reflects differences in loss severity across loans. This 
approach is also consistent with NAR's comment, because estimating the 
impact of seasoning on loss severity independently from its impact on 
defaults avoids duplicating seasoning's effect on credit losses.
(c) Household Liquidity
    NAR stated that liquidity of the household under stress is an 
important factor in the loss severity equation. OFHEO notes that for 
the single family loss severity analysis, the stress test considers 
housing-related liquidity of a household through loan seasoning. That 
is, updating the LTV provides some indication of the ability of 
borrowers to sell or borrow against their properties in order to 
provide liquidity. However, the stress test does not account directly 
for non-housing wealth or liquidity of borrowers. It is unclear how 
these factors could be measured or estimated accurately.
(d) Private Mortgage Insurance
    NAR also commented that the presence of private mortgage insurance 
is a variable that can influence the time to foreclosure and therefore, 
presumably, holding costs. OFHEO, however, has found insufficient 
evidence that the presence of mortgage insurance has any meaningful 
impact on foreclosure time. Both Enterprises submit their own 
foreclosure time guidelines to seller/servicers, which are independent 
of the presence of mortgage insurance. Accordingly, the presence of 
private mortgage insurance is not included as a variable in the loss 
severity equations.
    This issue is distinct from the question of how OFHEO should 
account for private mortgage insurance proceeds in the loss severity 
calculations. Several commenters noted that the loss severity 
calculation should deduct mortgage insurance proceeds from losses on 
loans covered by such insurance. OFHEO agrees that the loss severity 
calculation should account for mortgage insurance proceeds. This issue 
is discussed extensively in section III.C., Mortgage Credit 
Enhancements.
c. REO House Price Index
    In the ANPR, OFHEO asked what price index would be appropriate for 
REO properties. The question arose because defaulted loans generally 
have lower house-price appreciation rates than the market average, 
which is captured by HPI growth over time. After considering the ANPR 
comments and OFHEO's own research, OFHEO proposes an equation to relate 
actual declines in value for REO properties to changes in the HPI. This 
approach, which is described in section 3.5.3.3.3.1, Calculate Proceeds 
from Property Sale, of the Regulation Appendix, provides the 
information needed to predict accurately the loss of loan principal 
balance in loss severity calculations, but avoids the added complexity 
of creating a separate index.
    All five commenters that addressed this issue recognized that, 
without

[[Page 18142]]

adjustment, the HPI would not provide an adequate measure of REO price 
changes. However, none recommended creation of a separate REO index. 
Four commenters (MRAC, ACB, VA, and Freddie Mac) recommended modifying 
the general price index. MRAC suggested that a general HPI be used in 
conjunction with analysis of variances of prices to determine whether 
foreclosure prices have experienced slower appreciation or greater 
depreciation than the market average. ACB suggested that, rather than 
developing an REO price index, OFHEO study the ``left tail'' of the 
distribution of house prices in general. The term ``left tail'' refers 
to those houses with the smallest appreciation rates. S&P provided to 
OFHEO the rates of property value loss for foreclosures during the 
Great Depression.
    The proposed approach incorporates a statistical model based upon 
an analysis like that suggested by MRAC and ACB. The model predicts how 
far into the left tail each REO property value can be expected to be, 
relative to the outstanding mortgage balance, throughout the stress 
period. OFHEO's proposed approach essentially follows the specific 
recommendations of MRAC and ACB for modification of the HPI.
    The VA suggested using a general house price index, re-weighted to 
capture the regional distribution of REO properties. OFHEO agrees that 
regional differences in REO appreciation rates should be captured. The 
proposed regulation therefore incorporates Census division differences 
in historical HPI values and historical measures of the dispersion of 
house values around levels suggested by the HPI. See section 
III.A.4.d., Property Valuation.
    NAR did not recommend a specific approach, but cautioned that an 
REO price index might not be meaningful for Enterprise loans, because 
the Enterprises tend to sell REO properties quickly, thus limiting 
exposure to undue loss of value. For that reason, NAR recommended that 
any analysis of REO property values be based solely on Enterprise data. 
OFHEO also concurs with NAR that an REO price index built on non-
Enterprise data might be of limited usefulness for Enterprise loans. 
Given the richness and volume of the Enterprise data, and consistent 
with all other parts of the stress test, OFHEO has based the model of 
REO property values on Enterprise data. However, rather than developing 
a separate price index for REO properties, the proposed stress test 
models REO property value as a function of the path of the HPI. In 
addition, OFHEO proposes to adjust the resulting rate of loss of 
principal balance rate to reflect the fact that REO property values in 
the benchmark loss experience were lower in relation to the HPI than 
the REO property values in other Enterprise experience.
d. Multifamily Loss Severity
    With respect to loss severity, the stress test uses the same cost 
elements for multifamily loans as for single family loans. However, 
there is no loan seasoning, nor is statistical analysis used to 
determine loss of loan principal balance. All cost and revenue elements 
of multifamily loss severity rates are averages from Enterprise 
experience.
7. Relating Losses to the Benchmark Loss Experience
    The 1992 Act specifies that the stress test should apply rates of 
default and loss severity that are ``reasonably related'' to the 
highest rates experienced by the Enterprises for a period of at least 
two years in any contiguous areas having at least five percent of the 
nation's population (the benchmark loss experience).\129\ The stress 
test satisfies this reasonable relationship requirement in the context 
of two severe interest rate environments that are quite different from 
the interest rate environment of the benchmark loss experience. At the 
same time, the stress test also accounts for appropriate distinctions 
in credit risk across loan types and characteristics. OFHEO believes 
that the multivariate mortgage performance models developed by OFHEO 
are the best means of specifying loss rates for the wide variety of 
loans held by the Enterprises under the different interest rate 
scenarios specified in the statute. However, for reasons explained 
below, the models are adjusted to produce loss rates that are 
reasonably related to the losses experienced on the 30-year fixed-rate, 
single family mortgages in the benchmark time and place.
---------------------------------------------------------------------------

    \129\ 1992 Act, section 1361(a)(1) (12 U.S.C. 4611(a)(1)).
---------------------------------------------------------------------------

    Both Fannie Mae and Freddie Mac provided comments on how to 
implement a statistical model of mortgage performance that would be 
reasonably related to the benchmark loss experience. As discussed 
earlier, neither Fannie Mae nor Freddie Mac recommended a joint, 
multivariate statistical model of conditional default and prepayment 
rates. However, both discussed how other models could be used in the 
stress test and commented that a reasonable relation to the benchmark 
loss experience could be achieved by estimating those models solely on 
data from the benchmark loss experience.\130\ They noted that the 
advantage of limiting the statistical sample in that way is to allow 
the resulting equations to capture benchmark economic conditions 
without having explicit explanatory variables for economic conditions 
in the stress test.
---------------------------------------------------------------------------

    \130\ Fannie Mae recommended estimation of a statistical model 
of total terminations and Freddie Mac recommended estimation of a 
statistical model of prepayments only.
---------------------------------------------------------------------------

    The suggestion from Fannie Mae and Freddie Mac that the mortgage 
performance models be estimated solely with data from the benchmark 
loss experience, although appealing conceptually, turned out to be 
impractical. The benchmark loans comprise too small and homogeneous a 
set of loans to estimate models for all the Enterprises' current loans. 
Using a much larger sample of historical loan performance experience 
was important when estimating the statistical models, because it 
provided a wide variety of economic circumstances and mortgage 
experience upon which to base estimation of the model parameters. Like 
current Enterprise loan portfolios, the samples used to estimate the 
statistical equations include mortgages originated over many years and 
geographic locations, and having distributions across other factors of 
mortgage performance--such as age, coupon type or amortization terms--
that differ from those of the benchmark loans.
    The ``reasonable relationship'' requirement of the 1992 Act means 
that the adverse credit stress of the benchmark loss experience should 
be reflected in the stress test mortgage losses. However, when the 
mortgage performance models are applied unadjusted to a pool of loans 
with the same characteristics as the benchmark loans, using interest 
rate and house-price appreciation paths equivalent to those of the 
benchmark time and place, the resulting default and severity rates are 
slightly lower than the actual rates for the benchmark loss experience. 
This result should be expected, because the mortgage performance models 
are estimated from data on a broad range of historical experience, 
rather than just data from the benchmark loss experience. The benchmark 
loss experience was from the time and place with the worst mortgage 
losses for the Enterprises. Therefore it is reasonable to expect it to 
have default and severity rates somewhat higher than would be predicted 
based solely upon the explanatory variables used in the stress test. 
For this reason, the stress test

[[Page 18143]]

includes adjustments to the models to reflect more fully the additional 
stress of the benchmark experience.
    OFHEO proposes to relate losses projected by the statistical 
equations to the benchmark loss experience in two ways. First, 
benchmark house-price growth rates and multifamily (rental) market 
economic conditions that coincide with the time and place of the 
benchmark loss experience are applied to loans in the starting 
portfolio during the stress test period. Second, the default and 
severity rates predicted by statistical equations are increased, or 
``calibrated,'' to the benchmark loss experience rates, so that if 
newly originated loans with similar characteristics to those comprising 
the benchmark sample were subjected to the same economic circumstances 
as occurred in the benchmark loss experience, the statistical model of 
mortgage performance would project ten-year cumulative default and 
average severity rates equal to the rates actually observed for the 
benchmark sample.\131\ Under this approach, default and loss severity 
rates differ from the benchmark rates only to the extent interest 
rates, property values, and loan characteristics are different from the 
benchmark sample, or to the extent adjustments are necessary to account 
for other statutory requirements.\132\ Because of the addition of this 
benchmark ``calibration'' factor to default and loss severity 
equations, loss rates for all loans are slightly higher than would 
otherwise be projected.
---------------------------------------------------------------------------

    \131\ Loans comprising the benchmark sample were 30-year fixed-
rate loans.
    \132\ Differences in interest rates, property values, and loan 
characteristics can have very significant effects, however. The 
average mortgage credit loss rate for the two Enterprises in the 
benchmark sample was 9.4 percent. In the up-rate scenario of the 
stress test for June 1997, the average loss rate was 1.8 percent, 
while in the down-rate scenario it was 1.4 percent. The loss rate 
for the benchmark sample does not take account of mortgage insurance 
and other credit enhancements. Losses on benchmark loans after 
accounting for these receipts would have been seven percent.
---------------------------------------------------------------------------

    Although the principles for reasonably relating stress test losses 
to the benchmark loss experience are the same for single family and 
multifamily loans, the methods of reasonably relating losses to the 
benchmark differ and are discussed separately below.
a. Single Family Calibration
    For single family loans, calibration constants are added to default 
and loss severity rates.\133\ These constants are set forth in sections 
3.5.2.3.2.9 and 3.5.3.3.3 of the Regulation Appendix. Their development 
is described in section IV.B.8., Consistency with the Historical 
Benchmark Experience, of the Technical Supplement.
---------------------------------------------------------------------------

    \133\ The calibration constant used in the single family default 
rate equations is in addition to the particular product-type 
multiplier factors discussed earlier. The product-type multipliers 
relate other products to the benchmark 30-year fixed-rate loans, 
while the calibration constant relates all loans to the severe 
benchmark loss experience.
---------------------------------------------------------------------------

    The calibration constants were computed in three steps. First, all 
benchmark loans were assigned the same historical house-price 
experience--the ten-year sequence of appreciation rates from the OFHEO 
HPI for the West South Central Census Division, commencing in 1984, 
first quarter.\134\ Second, using the statistical equations estimated 
on a broader historical loan sample, OFHEO projected the ten-year 
experience of loans comprising the benchmark sample, computing the ten-
year cumulative default rate and ten-year average loss severity rate. 
These rates were measured in the same manner for the benchmark in 
NPR1.\135\ Third, these cumulative rates were compared to the actual 
cumulative default and prepayment rates computed for the benchmark in 
NPR1, and adjustment constants were calculated that, when applied in 
the models, would yield the equivalent default and loss severity rates.
---------------------------------------------------------------------------

    \134\ The West South Central Census Division does not exactly 
match the four-State benchmark region, but its use here to represent 
benchmark economics is consistent with OFHEO's proposal to aggregate 
data based on Census divisions and to apply historical Census 
division-level house price growth rates to season loans at the 
beginning of the stress test. What is most important is that the 
price series used to calibrate the statistical equations is the same 
series that will be used in the stress test itself. The actual ten-
year house-price experience of the West South Central Division and 
the four-State benchmark area, 1984-1993, are very similar.
    \135\ The ten-year cumulative default rate was computed as the 
sum of original UPBs for defaulted loans, divided by the sum of 
original UPBs for all loans in the sample. The average severity rate 
was calculated in similar fashion. Following the method used to 
identify the benchmark experience, the calibration procedure 
computes ten-year default and severity rates for each Enterprise 
separately, and then the two Enterprise-specific rates are averaged.
---------------------------------------------------------------------------

    The adjustment constant for loss severity rates is not applied to 
the entire loss severity rate, but rather to the loss of loan principal 
balance element of the loss severity rate. The constant is computed by 
subtracting the loss of loan principal balance that was predicted by 
the single family loss severity model from the loss of loan principal 
balance that occurred on defaulted loans in the benchmark loss 
experience. The second element of severity cost, transaction costs, was 
not adjusted to reflect benchmark conditions. OFHEO found it more 
appropriate in a national stress test to use a national blend of the 
institutional factors such as foreclosure costs, property management 
fees, and property sales expenses that comprise this element. The third 
element of loss severity cost, asset funding costs, enters the stress 
test as an imputed interest cost. As described in more detail in 
section 3.5.3 of the Regulation Appendix, this element is related to 
the benchmark loss experience through the use of foreclosure and 
property disposition event timing from the benchmark loss experience. 
The timing of these events determines the periods over which funding 
costs are calculated.
b. Relating Other Single Family Products to the Benchmark
    In the ANPR, OFHEO asked how to relate other types of mortgages to 
the benchmark, which was developed based on single family, 30-year, 
fixed-rate mortgages. The commenters' consensus was that some type of 
multiplier approach to alternative single family mortgages should be 
used, except for ARMs. These comments are discussed below.
(i) ANPR Comments
    NAR suggested that OFHEO develop statistical models of default for 
fixed- and adjustable-rate mortgages and relate the performance of 
other mortgage types to them. NAR also pointed out, however, that this 
type of relationship might be difficult to establish for new mortgage 
types for which there is insufficient historical experience. NAR 
suggested applying the benchmark default experience to these loans 
rather than measuring the difference in risk from the benchmark 
experience. VA addressed the same concern, suggesting that multipliers 
should be based on historical periods in which the other mortgage types 
had significant shares of the market. Specifically, VA suggested that 
measures of performance from those periods of other single family 
mortgage types relative to the 30-year, fixed-rate product could be 
used to impute the necessary performance differences from the benchmark 
loss experience to use in the stress test. Freddie Mac stated that any 
default-rate multipliers should be based on a broader range of 
Enterprise historical experience than the benchmark time and place.
    Freddie Mac, although recommending that OFHEO use simple 
multipliers, also raised a concern that loans receiving multiple 
multiplier factors could end up with unreasonably high stress test 
default rates. It cited, as an example, a balloon loan on an investor-
owned condominium. If the stress test were to apply default-rate 
multipliers for each of these three mortgage type categories

[[Page 18144]]

(condominium, investor-owned, and balloon), the combined risk factor 
premium could be unreasonably high. To remedy this problem, Freddie Mac 
recommended that the stress test incorporate limits on the interaction 
of risk factors.
    MRAC suggested that, if sufficient data were available, OFHEO might 
either create historical tables of default rates by various loan 
characteristics, in order to establish product-type multipliers, or use 
some type of regression analysis to discern performance differences 
among mortgage types. The MBA suggested that multipliers are the best 
approach because they are currently used by the Enterprises and 
therefore would provide a simple way for them to implement the risk-
based capital standards.
    OTS cautioned that multipliers might not be appropriate for ARMs or 
for multifamily loans, because the credit loss experience of these 
loans may not correlate well with that of fixed-rate, single family 
loans. OTS recommended that OFHEO consider using separate benchmarks 
for different types of loans. ACB, however, commented that there is no 
statutory requirement to incorporate the worst experience for each 
mortgage type into the stress test, and that a multiplier analysis for 
single family loan types would be sufficient.
    Consistent with its recommendation that OFHEO not develop a 
statistical model of conditional default rates, Fannie Mae suggested 
that multipliers be applied to (cumulative) loss rates, rather than to 
conditional default rates.
(ii) OFHEO's Response
    The stress test approach of adding product type adjustment factors 
as explanatory variables in a single family default equation is 
consistent with the multiplier approach recommended by commenters. 
However, the stress test approach does not have the shortcomings about 
which some commenters cautioned. It relies upon a broader historical 
experience than the benchmark sample alone to gauge the relative risk 
of other mortgage types, and it controls for the multiple multipliers 
problem outlined by Freddie Mac. The multiple multipliers problem is 
avoided because product type adjustment factors are estimated as part 
of the statistical default equation. The equation computes the marginal 
impact of each product type after controlling for all other explanatory 
variables. Using simple multipliers with limits on the amount of 
adjustment, as recommended by Freddie Mac, would either be too 
imprecise to reflect the relative risk of the loans that fall into 
multiple product type categories, or else would become as complex as a 
statistical model in order to account for all of the conceivable 
combinations of product types.
    OFHEO agrees with the OTS comment that a multiplier approach is not 
appropriate for ARMs. Equations for single family default and 
prepayment rates in the stress test are, therefore, estimated 
separately for ARMs. This is appropriate because the adjustable payment 
features of these loans create unique incentives to either default or 
prepay that are not found in other mortgage types. The ARM default 
equation does, however, receive the same benchmark calibration constant 
used in the other two single family default equations. The use of this 
constant reasonably relates ARMs to the added stress of the benchmark 
loss experience in a manner consistent with how other single family 
product types are related to the benchmark loss experience.
c. Relating Multifamily Mortgage Performance to the Benchmark
    In the ANPR, OFHEO requested comment on how the stress test 
multifamily mortgage performance should be related to the single family 
benchmark. Respondents to the ANPR mentioned the need to capture the 
different underwriting variables and economic factors that would 
influence multifamily performance directly. They warned against 
applying multipliers to single family losses to generate multifamily 
losses. These concerns were raised by OTS, MBA, Fannie Mae, and Freddie 
Mac. In addition, OTS and Fannie Mae suggested that OFHEO may need to 
explore options other than relating stress test credit losses on 
multifamily loans to the single family benchmark.
    OFHEO agrees with the commenters' concerns about using a simple 
multiplier approach for multifamily loans, and proposes instead a 
separate statistical model of multifamily mortgage performance based on 
multifamily market conditions, property financial characteristics (DCR 
and LTV), and loan terms--whether fully amortizing or balloon, or 
having fixed or adjustable interest rates. The statistical model allows 
the application of OFHEO's first principle, outlined above in section 
III. A. 5. e., Choice of Explanatory Variables for Default and 
Prepayment, for relating stress test losses to the benchmark: using 
economic conditions of the benchmark experience in the stress test. 
OFHEO believes that multifamily rent and vacancy indexes from the 
benchmark time and place provide the best means to relate starting 
multifamily loan portfolios to the benchmark loss experience. These 
indexes account for the economic decline that occurred in the benchmark 
region in the economic factors that affect multifamily mortgage credit 
risk. Therefore, the stress test creates a reasonable relationship to 
the benchmark loss experience by using vacancy rates from and percent 
changes in rents from the benchmark loss experience to update property 
financials (DCR and LTV) throughout the stress period.
    Because of the small number (13) of multifamily loans purchased by 
the Enterprises in the benchmark region during 1983 and 1984, it is not 
possible to compute calibration adjustments like those in the single 
family default and severity equations. Instead, OFHEO proposes to treat 
all defaults as full foreclosure events and apply loss severity rates 
without consideration of loan seasoning. The effect of this approach is 
to create higher credit losses than if the stress test were to account 
for multifamily defaults that are resolved without foreclosure and 
adjust severity rates to account for the age of loans.
    Methodologically, treating all multifamily defaults as foreclosure 
events is consistent with OFHEO's proposed approach to single family 
credit loss generation in the stress test. However, OFHEO is aware that 
use of various default resolution strategies other than foreclosure 
(loss mitigation) played an important role in controlling multifamily 
default losses in the severe environment of the late 1980s and early 
1990s. Therefore, accounting for loss mitigation in the stress test 
would tend to decrease losses for any given economic conditions. 
Treating all defaults as foreclosures for calibration purposes, rather 
than allowing for loss mitigation efforts, results in an increase in 
loss severity--before application of any credit enhancements--of 6.5 
percent per defaulting loan.\136\
---------------------------------------------------------------------------

    \136\ The 6.5 percent figure is arrived at by multiplying the 13 
percent of defaults resolved with alternatives to foreclosure by a 
50 percent loss rate reduction factor.
---------------------------------------------------------------------------

    There is an exception to the rule of treating all defaults as 
foreclosure events for Enterprise loan programs that require the 
seller/servicer to repurchase loans that become 90-days delinquent. For 
loans in these programs, the recorded ``default'' event at the 
Enterprises is the point at which a loan becomes 90 days delinquent, 
rather than a foreclosure-like event where the Enterprise obtains title 
to the collateral property.

[[Page 18145]]

    The stress test loss severity rate for these loans is 39 
percent.\137\ The 39 percent loss severity rate reflects experience of 
the Enterprises during the stressful conditions of the early 1990s, 
including approximately 50 percent cures (or modifications) and 50 
percent foreclosures on 90-day delinquencies. OFHEO research indicates 
that this is a reasonable approximation for the stress test.
---------------------------------------------------------------------------

    \137\ This rate is discounted by 12 months to reflect the 
average time from the default date (30 days after last paid 
installment date) to final resolution.
---------------------------------------------------------------------------

8. Inflation Adjustment
    The 1992 Act specifies that, to the extent that the ten-year CMT 
increases by more than 50 percent over its average for the nine months 
preceding the starting date of the stress test, credit losses must be 
adjusted ``to reflect a correspondingly higher rate of general price 
inflation.'' \138\ In the stress test, mortgage credit losses are not 
related to rates of general price inflation, but most are related to 
rates of house price inflation.\139\ Implementing this provision of the 
statute requires consideration of the relationship between interest 
rates, general inflation rates, and house price inflation rates.
---------------------------------------------------------------------------

    \138\ 1992 Act, section 1361(a)(2)(E) (12 U.S.C. 4611(a)(2)(E)).
    \139\ Multifamily credit losses are related to rent growth 
rates. The same adjustment described here for house price inflation 
rates is also made to rent inflation rates.
---------------------------------------------------------------------------

    These relationships are complex. Over recent decades, changes in 
broad inflation measures generally have preceded changes in interest 
rates in the same direction. And changes in interest rates have been 
accompanied by changes in house price inflation rates in the opposite 
direction. Thus, over short and intermediate periods of time, interest 
rates and house price inflation rates have often moved divergently. For 
example, consider the three five-year periods beginning in 1975. From 
the beginning of 1975 to the end of 1979, the ten-year CMT averaged 
about 8 percent, while house prices rose at an 11 percent annual rate. 
In the following five-year period, from 1980 to 1984, interest rates 
were 50 percent higher (12 percent), while house price inflation fell 
to 4 percent. Then in the third five-year period, 1985 to 1989, 
interest rates declined to 9 percent, while house price gains 
accelerated to 7 percent.\140\ Over longer periods of time, however, 
these changes have tended to reverse themselves. For periods of ten 
years or more, higher (lower) than average interest rate levels have 
generally been associated with higher (lower) than average rates of 
general inflation and house price inflation.
---------------------------------------------------------------------------

    \140\ General inflation rates (based on the CPI) followed a 
still different pattern. They averaged 8 percent per year during the 
first five-year period, 7 percent in the second, and 3 percent in 
the third five-year period.
---------------------------------------------------------------------------

    In unusual environments, such as those represented by the economic 
conditions of the stress test, average past relationships between 
interest rates, general inflation rates, and house price inflation 
rates may not prevail. The nature or cause of the projected mortgage 
credit stresses in the stress test are not specified in the statute. 
They could involve problems particular to housing markets, such that 
house price behavior deviates persistently from general inflation 
patterns. Or they could be focused on non-house-price factors, such as 
unemployment, relocation, or divorce rates.
    Except to the extent that the ten-year CMT rises in the up-rate 
scenario by more than 50 percent, the stress test does not project any 
differences in house price changes or other sources of credit stress in 
the two interest rate scenarios. And, aside from the inflation 
adjustment, the specific pattern of house price changes used in both 
scenarios is not designed to be consistent with any particular pattern 
of interest rates. It was chosen to replicate (and encapsulate in one 
variable) the overall level of credit stress in the benchmark loss 
experience.
    In order to implement the statutory requirement, the stress test 
projects that cumulative increases in house prices, a component of 
general inflation, are higher in the up-rate scenario by an amount that 
reflects, percentage point for percentage point, any positive 
difference between the ten-year CMT and the level corresponding to a 50 
percent increase. Thus, for example, if the ten-year CMT starts at 6 
percent and increases by 75 percent to 10.5 percent, the increase in 
excess of 50 percent is 1.5 percentage points. The cumulative change in 
house prices during the up-rate scenario would equal the cumulative 
change during the down-rate scenario plus an upward adjustment. The 
adjustment is the amount needed to reflect what the cumulative increase 
would be if the house price inflation rate were 1.5 percent higher, on 
average, throughout the part of the stress period in which the ten-year 
CMT exceeds 9 percent.\141\
---------------------------------------------------------------------------

    \141\ The stress test would calculate the cumulative adjustment 
factor in this case to be 1.0159\1/6\, so final house 
price levels in the up-rate scenario would be 14.6 percent higher 
than they would be in the down-rate scenario. In this formula, 9\1/
6\ represents the number of years the ten-year CMT exceeds 9 percent 
by the full 1.5 percentage points plus two months to reflect the 
period in which the ten-year CMT exceeds 9 percent by a smaller 
amount. If the ten-year CMT increases 75 percent over the base 
month, a 50 percent increase will be achieved by month eight. The 
full increase will be achieved by month 12. For the purposes of this 
calculation, the result is the same as it would be if the extra 25 
percent lasted for nine years and two months.
---------------------------------------------------------------------------

    In recognition of the likely short- and intermediate-term 
divergence between interest rates and house price behavior, the stress 
test concentrates all of the adjustment in the final five years of the 
stress period. Thus, house prices are identical in the two stress test 
interest rate scenarios during the first five years, but increase much 
more rapidly in the last five years of the up-rate scenario than they 
do in the down-rate scenario.
    Several respondents to OFHEO's ANPR commented on this issue. VA 
opposed any adjustment, arguing that while the long-term behavior of 
house price inflation and general inflation is consistent, the short-
term relationship is weak, and the relationship between interest rates 
and house prices ``is even more tenuous.'' VA further agrees that 
specific economic conditions can disrupt any general relationships, and 
that an adjustment would be inconsistent with the approach of private 
rating agencies. OFHEO believes, however, that some adjustment is 
required by the statutory language.
    HUD argued that adjusting the rate of increase in house prices 
throughout the stress period on a one-to-one basis with general price 
inflation would deny the role of changes in real interest rates over 
time. HUD suggested that OFHEO consider current trends and long-run 
relationships between real interest rates and house prices. NAR 
suggested that a one-to-one relationship is appropriate for long-term 
assumptions, and ACB commented similarly. OFHEO believes that its 
approach, which uses a one-to-one relationship for the cumulative 
change but concentrates the change in the last five years of the stress 
period, is not inconsistent with any of these recommendations.
    Freddie Mac recommended that house price inflation should vary with 
interest rates in a one-to-one relationship, not only with respect to 
increases in the ten-year CMT exceeding 50 percent, but also with 
respect to all interest rate changes. House price inflation rates would 
be based on rates current at the start of the stress period and rise or 
fall by amounts equal to the change in the ten-year CMT in both 
scenarios. Such an approach could result in more severe credit losses 
in the down-rate scenario and very few credit losses in the up-rate 
scenario. OFHEO believes that the stress test should reflect the 
possibility that substantial credit losses would occur in either 
scenario. The recommended

[[Page 18146]]

approach also would not have any obvious relationship to the benchmark 
loss experience. Applying the approach at the time the benchmark loans 
were originated would result in much stronger house price growth than 
actually occurred in the benchmark area.
    Freddie Mac further argued that a stress test that incorporated a 
ten-year CMT that exceeded the rate of house price appreciation by more 
than 6.5 percentage points over a ten-year period would be inconsistent 
with national historical experience and, therefore, inappropriate. 
However, national historical experience is not an appropriate criterion 
for the stress test's key source of mortgage credit stress. Credit 
losses in the stress test are required to exceed national historical 
experience. They are based on the worst regional, not national, 
experience.\142\ More importantly, as discussed above, house price 
projections in the stress test are not designed to correspond to any 
particular interest rate level. Rather, they are simply a means of 
incorporating an overall credit stress level that is comparable to the 
benchmark loss experience and which may reflect stresses from a variety 
of non-house price sources not explicitly included in the mortgage 
performance model.
---------------------------------------------------------------------------

    \142\ The average ten-year CMT exceeded average house price 
growth in the West South Central Division during the 1980s by 9.5 
percentage points. For the benchmark loss experience, the difference 
was 8.5 percentage points.
---------------------------------------------------------------------------

B. Interest Rates

    The 1992 Act specifies the level of the constant maturity Treasury 
yield (CMT) for ten-year securities during the last nine years of the 
stress period.\143\ However, only general guidance is provided for the 
levels of yields on Treasury securities with different maturities. 
Also, yields on other financial instruments are not explicitly 
mentioned. The behavior of yields on financial instruments other than 
ten-year Treasury securities will have potentially substantial and 
pervasive effects on the Enterprises during the stress period. Those 
yields will determine the cost of new debt issued and earnings on new 
investments, as well as the interest rates paid or earned on assets, 
liabilities, or derivatives contracts that are tied to market yield 
indexes. They will also have a significant effect on the volumes of 
mortgage prepayments and defaults. The magnitude of the effects on an 
Enterprise during the stress period will depend greatly on the 
Enterprise's funding strategies at the start of the stress period.
---------------------------------------------------------------------------

    \143\ 1992 Act, section 1361(a)(2) (12 U.S.C 4611(a)(2)).
---------------------------------------------------------------------------

1. Yields on Treasury Securities
a. Statutory Requirements
    The 1992 Act describes two interest rate scenarios (one rising and 
one falling) based on movements in the ten-year CMT. In the rising or 
up-rate scenario, the ten-year CMT increases during the first year of 
the stress test period and then remains constant at the greater of: (1) 
600 basis points above the average yield during the preceding nine 
months; or (2) 160 percent of the average yield during the preceding 
three years. However, in no case may the yield increase to more than 
175 percent of the average yield over the preceding nine months. In the 
falling or down-rate scenario, the ten-year CMT decreases during the 
first year of the stress period and then remains constant at the lesser 
of: (1) 600 basis points below the average yield during the preceding 
nine months; or (2) 60 percent of the average yield during the 
preceding three years. However, in no case may the yield decrease to 
less than 50 percent of the average yield over the preceding nine 
months.
    The 1992 Act does not specify the shape of the yield curve during 
the stress period. Rather, it simply requires that the levels of other 
Treasury yields ``change relative to the 10-year Constant Maturity 
Treasury (CMT) yield in patterns and for durations that are reasonably 
related to historical experience and are judged reasonable by the 
Director.'' \144\ The statute also does not specify the manner in which 
the ten-year CMT moves during the first year of the stress period to 
reach the level required for the remainder of the period.
---------------------------------------------------------------------------

    \144\ 1992 Act, section 1361(a)(2)(D) (12 U.S.C. 4611(a)(2)(D)).
---------------------------------------------------------------------------

    In its comments to OFHEO's ANPR, ACB suggested that OFHEO consider 
using stochastic projections of all interest rates, if OFHEO determined 
that stochastic projections were consistent with statutory 
requirements. ACB noted that the process could be constrained to insure 
that the ten-year CMT reached its required level during the final nine 
years of the stress period on an average basis. OFHEO has determined 
that such an approach would not be compatible with the 1992 Act. That 
statute clearly specifies that the ten-year CMT will be constant during 
the final nine years of the stress period. Furthermore, as Fannie Mae 
commented, using a stochastic model for determining interest rates 
would create unnecessary uncertainty about what amount of capital would 
actually be required for a given set of risk positions. A stochastic 
model also would add unnecessary complexity to the regulation. 
Accordingly, OFHEO proposes that all interest rates during the stress 
period be fully determined by past data on interest rates.
b. Yields of Other Treasury Maturities During the Final Nine Years
(i) Constant or Varying Yields
    OFHEO considered whether the Treasury yield curve should be 
constant over the final nine years of the stress period or whether it 
should change in some specific manner. OFHEO proposes to use a constant 
yield curve. While yields are extremely unlikely to remain constant or 
even roughly so over a period as long as nine years, there are no 
serious disadvantages to using such an approach in the stress test, and 
there are compelling advantages.
    A constant yield curve is a straightforward approach that is 
consistent with the statutory specification of a constant ten-year CMT. 
The purpose of the interest rate component of the stress test is to 
assess an Enterprise's ability to withstand a prolonged shift to a much 
higher or much lower interest rate environment. No specific pattern of 
yield changes can fully capture the range of possible future adverse 
changes. Based on historical experience, one would expect all interest 
rates to fluctuate over a broad range during a period as long as nine 
years. Different underlying macroeconomic circumstances would be 
associated with different evolutions of the entire yield curve, 
including the ten-year CMT. Tying the stress test to one specific set 
of macroeconomic circumstances would tend to limit its general 
usefulness. The real-life danger the Enterprises face of much higher or 
much lower interest rates during the next decade is not focused on any 
particular portion of that ten-year period. Designing a stress test 
with any specific pattern of interest rate changes after the first year 
of the stress period would imply a belief that Enterprise risk 
exposures in some future years would be a matter of greater public 
concern than in other years. While an argument could be made that near-
term risk exposures would create losses with a higher present value, 
that concern should be balanced by a recognition that the risk of a 
very different interest rate environment is greater for distant years 
than for the near-term.
    A stress test with interest rates that are especially high or low 
in particular

[[Page 18147]]

future years would encourage Enterprise hedging strategies to focus on 
those specific years. Risks in other years, when stress test 
projections were more moderate, might receive relative neglect. The 
Enterprise would thus be providing more protection against more 
adverse, but less likely, interest rates in some years at the expense 
of less protection against less adverse, but more likely, interest 
rates in other years. Such an incentive would provide less general 
protection and thereby increase the risk of failure.
    In their ANPR comments, Fannie Mae and VA suggested specific fixed 
yield curves, consistent with OFHEO's proposal in this regard. Freddie 
Mac recommended a considerably more complex approach that would 
generally result in relatively more adverse short-term interest rates 
in the early part of the final nine years of the stress period and less 
adverse short-term interest rates later. OFHEO believes its proposal is 
much simpler and will provide better general protection against 
Enterprise failure for the reasons discussed above.
    Freddie Mac argued that a fixed yield curve would be unreasonable 
for two reasons. First, Freddie Mac stated that a fixed curve would be 
inconsistent with the statutory requirements that changes in yields on 
Treasury securities with maturities other than ten-years ``will change 
relative to the 10-year constant maturity Treasury yield in patterns 
and for durations that are reasonably related to historical 
experience.'' It is clear from the legislative history that Congress 
did not intend to prohibit constant yield curves, per se, but rather 
wanted to prohibit unusual yield curves lasting for a longer time than 
could be reasonably related to historical experience. The language of 
the statute follows the original Senate-passed bill, except that 
``reasonably related to'' in the quoted phrase was substituted for 
``within the range of,'' and a specific restriction on unusual yield 
curves was removed. The Senate Committee, in explaining its 
understanding of the yield curve provision, actually recommended that 
the yield curve be fixed during at least the final five years of the 
stress period.\145\
---------------------------------------------------------------------------

    \145\ S. Rep. No. 102-282, at 22 (1992).
---------------------------------------------------------------------------

    Second, Freddie Mac argued that a constant yield curve ``would be 
of little value in measuring the ability of an Enterprise to absorb 
losses in relation to its risks'' because interest rate volatility 
would disappear and the prices of options would approach zero. Market 
estimates of interest rate volatility, however, play no important role 
in the stress test OFHEO is proposing. The Enterprises are not 
projected to buy or sell any options, as this is a ``no new business'' 
stress test. While option value does affect decisions about option 
exercise, and those decisions are an important element of the stress 
test, the interest rate movements in the stress test are quite large. 
In such circumstances, Enterprise decisions about option exercise will 
generally be relatively insensitive to precise measures of option 
value. Homeowners' decisions to exercise their options to prepay their 
mortgages are also based on past homeowner responses to large changes 
in interest rates and not on specific measures of volatility. Stress 
test projections relating to the exercise of options implicitly assume 
that expectations about volatility are within normal ranges, despite 
the lack of change in interest rates. The proposed approach is an 
efficient simplification that does not distort Enterprise risks in any 
meaningful way.
(ii) Choice of Fixed Yield Curve Shapes
    OFHEO proposes that all Treasury yields for key maturities (three-
and six-month; one-, three-, five-, and 20-year) in the final nine 
years of the up-rate scenario be equal to the ten-year CMT. In the 
final nine years of the down-rate scenario, OFHEO proposes that all key 
Treasury yields have the same ratio to the ten-year CMT that they had, 
on average, during the nine-year period from May 1986 through April 
1995. The proposed yield curves for both interest rate scenarios 
correspond to historical experience.
    OFHEO based its selection of yield curves on an examination of 
historical data on Treasury yields. Data are available starting in 
December 1958. OFHEO focused on the relationship between a short-term 
(six-month) yield and the ten-year yield.\146\ From 1959 through 1996, 
the average yield curve slope, measured by the ratio of the six-month 
CMT to the ten-year CMT, was 0.88, a moderate upward slope. However, 
when calculated on a monthly basis, this slope has varied considerably 
through time (See Table 26, Frequency Distribution of Yield Curve 
Slopes, 1959--1996). Monthly slopes have been as low as 0.48 (September 
and October 1992) and as high as 1.29 (March 1980). In more than half 
of the months, yield curves were roughly flat or downward sloping 
(slopes above 0.95) or were steeply upward sloping (slopes below 0.75).
---------------------------------------------------------------------------

    \146\ In the following discussion, yields of six-month Treasury 
bills are expressed on a bond-equivalent basis. The six-month 
maturity has the advantage that the timing of its payments are 
consistent with the interest rate payment cycle of Treasury notes 
and bonds, ensuring comparability of yields across maturities.

[[Page 18148]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.211


    Of particular relevance are the average slopes over periods of 108 
months (nine years) and their relationship to previous increases or 
decreases in yields. Ratios of the average six-month Treasury CMT to 
the average ten-year CMT for periods of 108 months ranged from 0.77 
(for periods ending from January 1994 through April 1996) to 0.99 (for 
periods ending from September 1981 through June 1982). OFHEO must 
project yields curves for a nine-year period in which the ten-year CMT 
has increased by 75 percent, and decreased by 50 percent, from its 
average in the nine months ending one year before the beginning of the 
nine-year period.\147\ Accordingly, OFHEO sought to determine whether 
historical data suggest any relationship between changes in average 
ten-year CMT and yield curve slopes for relevant time periods.
---------------------------------------------------------------------------

    \147\ In high yield environments, the changes in interest rates 
would be somewhat smaller, but past and recent data suggest that the 
changes will generally be of this magnitude.
---------------------------------------------------------------------------

    At no time during the past 40 years have ten-year CMTs changed as 
greatly as required in the stress test. The largest comparable increase 
was 56.3 percent from the nine-month average of 6.04 percent during 
November 1971 to July 1972 to the nine-year average of 9.44 percent 
during August 1973 to July 1982. The ratio of six-month to ten-year 
yields during the later period was 0.98. The largest comparable 
decrease was 38.9 percent from the nine-month average of 12.74 percent 
during February to October 1984 to the nine-year average of 7.78 
percent during November 1985 to October 1994. That change was 
associated with a slope of 0.77 during the nine-year period.
    The pattern of relatively flat yield curve slopes after interest 
rate increases and steep yield curve slopes after interest rate 
decreases is consistent with the data. In all nine-year periods in 
which the average ten-year CMT was above its average during the 
relevant earlier nine-month period, the yield curve slope was greater 
than 0.87. In all nine-year periods in which the average ten-year CMT 
was below its average during the relevant earlier nine-month period, 
the yield curve slope was less than 0.87. Furthermore, the greater the 
increase in the ten-year CMT, the flatter the yield curve slope tended 
to be, and the greater the decrease in the ten-year CMT, the steeper 
the yield curve slope tended to be. Results of an ordinary least 
squares regression imply that a sustained 75 percent increase in the 
ten-year CMT would likely result in a CMT yield curve slope of 1.00, 
while a sustained 50 percent decline provides an expected slope of 
0.77.\148\
---------------------------------------------------------------------------

    \148\ An ordinary least squares regression describes the results 
quantitatively. The dependent variable (Yt) is the ratio 
of the average six-month CMT to the average ten-year CMT during the 
nine years ending in month t. The independent variable 
(Xt) is defined as the ratio of the average ten-year CMT 
in the nine years ending in month t to the nine-month average of the 
ten-year CMT from month t-128 to month t-120. The regression results 
are: Yt = 0.86 + 0.19 Xt.
    Although this regression is based on monthly data over a 38-year 
period, it is a small data set for investigating this issue. The 
yield data start in December 1958, but each observation needs 128 
months prior data, so the first observation used in the regression 
is August 1969. That leaves 326 observations through September 1996, 
but because of the lags, each observation is very similar to the one 
preceding it. There are really only four fully separate dependent 
variable observations. In these circumstances, the coefficient 
estimates are unbiased, but the usual regression statistics are not 
meaningful. In an alternative regression, the data were reorganized 
as follows. The 326 observations were rank-ordered by the 
independent variable and divided into quartiles. Using average 
values of the two variables from each quartile, the regression was 
rerun with the resulting four observations. The results are: 
Yt = 0.86 + 0.20 Xt.
    Differences in parameter estimates from the full sample 
regression were small, less than 0.01, and the standard error of the 
coefficient of Xt was 0.022. Even though the observations for these 
regressions were limited, to the extent the data do exist, they 
support OFHEO's yield curve proposal.
---------------------------------------------------------------------------

    If the macroeconomic circumstances associated with a future shift 
in yields were to differ from those that engendered interest rate 
changes in recent decades, different results might easily occur. 
Nevertheless, the historical experience of the past four decades, as 
indicated both by the actual yield curve slopes in the episodes when 
the ten-year CMT changed most greatly and by the more general results, 
suggests an essentially flat yield curve in the up-rate scenario, and a 
curve with a relatively steep upward slope in the down-rate scenario.
    Although the highest yield curve slope was 0.99, OFHEO chose a more 
straightforward yield curve slope of 1.00 for the up-rate scenario. The 
largest historical interest rate increase resulted in an almost flat 
yield curve, and that increase was still well below the increase of the 
up-rate scenario of the stress test. In addition to the six-month 
yields, OFHEO also proposes that all other key Treasury yields be equal 
to the ten-year CMT in the up-rate scenario. When the six-month CMT 
equals the ten-year CMT, setting all the other key

[[Page 18149]]

Treasury yields equal to the same levels is straightforward and 
appropriate. In the down-rate scenario, however, setting the six-month 
and the ten-year yields does not directly suggest appropriate rates for 
instruments with other maturities. OFHEO proposes in this scenario that 
slopes of key CMTs to the ten-year CMT be based on a specific 
historical experience in a straightforward way that incorporates long-
term relationships between yields of instruments with different 
maturities. The slope of the average six-month CMT to the average ten-
year CMT during the nine-year period ending in April 1995 closely 
approximates the yield curve slope suggested by the regression 
equation.
    Several commenters responded to a question in OFHEO's ANPR about 
the Treasury yield curve. Consistent with OFHEO's proposal, Fannie Mae 
recommended that OFHEO focus its approach to projecting yield curves on 
the ratio of the six-month Treasury yield to the ten-year Treasury 
yield. However, Fannie Mae recommended that the ratio of the six-month 
CMT to the ten-year CMT be set at a long-run historical average in both 
interest rate scenarios. Such an approach would not be consistent with 
actual experience that large sustained interest rate increases are 
accompanied by relatively flat yield curves and that large, sustained 
interest rate decreases are accompanied by relatively steep yield 
curves.
    The Department of Veterans Affairs recommended a yield curve 
formula that would depend heavily on the shape of the yield curve at 
the start of the stress test. OFHEO considered such an approach, but 
found no evidence in historical data that the yield curve shape at the 
start of a ten-year period is related to the average shape over the 
final nine years of that period.
    Freddie Mac suggested an approach based on an assumption that the 
statutory changes in interest rates represent a ``regime shift.'' As 
market participants adjust to the new regime, Freddie Mac argued, 
average yield curve relationships should return. OFHEO believes it is 
more appropriate to base projections of yield curve relationships on 
what has actually occurred in the past with the most similar changes in 
ten-year CMT levels.
    NAR recommended that OFHEO take into account Treasury refunding 
behavior during the stress period. In order to keep the stress test as 
general as possible, OFHEO chose not to make any specific projections 
about Treasury debt issuance during the stress period.
c. Yields of Treasury Securities During the First Year
    OFHEO proposes that during the first year of the stress period, the 
yields on Treasury securities of all maturities adjust linearly from 
their levels in the month proceeding the stress period to their levels 
during the final nine years of the stress period. In comments to 
OFHEO's ANPR, Fannie Mae stated that movements of the six-month and 
ten-year CMTs should be consistent during an adjustment period of one 
to two years. OFHEO agrees and believes its proposal will result in 
sufficiently consistent movement.
    Freddie Mac suggested an approach under which, before the end of 
the first year, the yield curve might invert in the up-rate scenario 
and become very steeply upward sloping in the down-rate scenario. As 
previously discussed, OFHEO believes this approach is unnecessarily 
complex.
2. Yields of Non-Treasury Instruments
a. In General
    Payments during the stress period associated with many Enterprise 
assets, liabilities, and derivatives contracts and the performance of 
mortgages, especially prepayment behavior, are dependent on future 
levels of yields on non-Treasury instruments and levels of non-Treasury 
interest rate indexes. OFHEO proposes to project these yield levels 
using econometric models relating non-Treasury interest rate series to 
yields on Treasury securities of comparable maturity.
    The econometric specifications were based on two primary criteria. 
First, whenever possible, the non-Treasury interest rate series were 
modeled using the relative (rather than absolute) spread over 
comparable CMTs. Second, the specifications balanced the desire for 
simplicity with the need to account for the time-series properties 
inherent in the data.
    Autoregressive integrated moving average (ARIMA) models were used 
to model the behavior of the non-Treasury interest rate series.\149\ 
The models capture the average historical relationships between 
specific CMTs and non-Treasury interest rates. OFHEO believes this 
approach is consistent with recommendations of all commenters to a 
question on this issue in OFHEO's ANPR.
---------------------------------------------------------------------------

    \149\ An ARIMA (p,d,q) model implies p autoregressive terms, d 
differences of the original series, and q moving average terms. 
Generally speaking, differencing is undertaken to render a series 
``mean-stationary,'' which is a requirement for statistical analysis 
of autoregressive models. For example, observations from a random 
walk include the cumulative effect of all past shocks (random 
disturbances) and/or trends. Differencing can net out the effect of 
persistent movements and make a series stationary. Autoregressive 
terms also represent the persistence of past shocks, but where the 
effect of the shock diminished over time. Moving average terms 
represent the effects of shocks that disappear completely after some 
finite number of periods.
    In some situations the original series may also exhibit non-
stationarity in the variance, requiring other normalizing 
transformations (e.g., taking logarithms). Also, visual examination 
of the data series and residual analysis based on appropriate 
statistical criteria (e.g., Ljung-Box Q-statistics) were used to 
guide the model selection process.
    In some cases, a constant term has been included. This has the 
effect of preserving the historical average relative spread between 
the index and the corresponding Treasury rate when projecting future 
values. This is only done when there is some evidence that this 
historical difference is statistically significant. While 
differencing is necessary in many models to achieve stationarity in 
the mean, the use of relative spreads over Treasury rates of 
comparable maturities generally appears to make the original 
relative rate series variance stationary.
---------------------------------------------------------------------------

b. Yields on Enterprise Debt
    OFHEO proposes that yields on Enterprise debt be projected in the 
same manner as yields on other non-Treasury instruments, except that a 
50 basis point premium is added after the first year of the stress 
period. After one year of stress test conditions, the Enterprises might 
appear strong based on accounting measures of earnings and net worth. 
However, market values of the Enterprises' assets, liabilities, and 
derivatives contracts would fully reflect the effects of the interest 
rate shock and some of the credit quality deterioration of the stress 
test. Investors would be aware of these changes in market value and 
adjust their evaluations of the Enterprises' financial health 
accordingly. Because the Enterprises' ability to withstand further 
interest rate and credit shocks likely would be low, the Enterprises in 
the final nine years of the stress period would likely not meet their 
risk-based capital requirement and would, therefore, be subject to 
dividend restrictions. Such events might strengthen investor concerns 
about the Enterprises' financial health.
    As government sponsored enterprises, the Enterprises likely would 
suffer much smaller debt market penalties than fully private firms in 
the same circumstances. However, the historical experiences of Fannie 
Mae and the Farm Credit System during periods of financial stress 
strongly suggest that borrowing costs would include some risk premium 
during economic conditions such as those in the stress test. As 
illustrated by data reported in the General Accounting Office's 1990 
report on government sponsored enterprises, Fannie Mae's short-term

[[Page 18150]]

borrowing costs during 1980 through 1982 were generally about 80 basis 
points in excess of yields on comparable maturity Treasury debt, rising 
at one point to 200 basis points above Treasury yields. Spreads receded 
after sharp declines in interest rates greatly improved Fannie Mae's 
condition to a more normal range centered roughly at 20 basis points. 
Spreads were high again in the late 1980s for both Fannie Mae and the 
Farm Credit System, ranging from 40 to 100 basis points over a two-year 
period during the Farm Credit System's time of greatest financial 
difficulty.\150\
---------------------------------------------------------------------------

    \150\ U.S. General Accounting Office (1990), Government 
Sponsored Enterprises: The Government's Exposure to Risk, 
Washington, DC: U.S. General Accounting Office, (GAO/GGD-90-97) 87-
88.
---------------------------------------------------------------------------

    In stress test simulations based on the quarter ending in June 
1997, the Enterprises' borrowing costs, including the 50 basis point 
premium, are 78 basis points above comparable Treasury yields in the 
up-rate scenario and 56 basis points above in the down-rate scenario 
after the first year of the stress period. Such spreads are appropriate 
because it is essential that the Enterprise be adequately prepared for 
widening debt yield spreads in periods of financial stress.
    In its comments to OFHEO's ANPR, ACB pointed to Fannie Mae's 
difficulties in 1980 to 1982 as a possible basis for assessing likely 
borrowing spreads in the stress period. ACB also suggested that OFHEO 
might consider projecting the Treasury Department's use of its 
statutory authority to lend money to the Enterprises in stressful 
circumstances. OFHEO believes the stress test should assess the 
Enterprises' abilities to withstand the stress test without borrowing 
from the Treasury Department.
    Freddie Mac commented that OFHEO should assume that the market's 
perception of an implicit government guarantee on Enterprise debt 
protects the Enterprises against any increased risk premium in 
borrowing spreads. OFHEO disagrees and believes the historical evidence 
is inconsistent with that view. OFHEO does agree that financial 
weakness of the Enterprises during the stress period should not be 
expected to have the same effect on borrowing costs that it would for 
firms that are not government sponsored enterprises. Nonetheless, some 
increase in risk premiums is appropriate. As the Enterprises' offering 
prospectuses clearly state, Enterprise obligations are not backed by 
the full faith and credit of the Federal government. OFHEO also agrees 
that attempting to calculate appropriate borrowing spreads at different 
times during the stress test, based on specific measures of Enterprise 
stress, would unnecessarily complicate the test. Accordingly, OFHEO 
proposes a constant risk premium during the final nine years of the 
stress period.

C. Mortgage Credit Enhancements

1. Background
    The Enterprises use mortgage credit enhancements to reduce their 
credit risk exposure. For single family loans with LTV ratios in excess 
of 80 percent, the Enterprises must use certain statutorily enumerated 
credit enhancements. The Charter Acts prohibit the purchase of 
conventional single family mortgages with LTV ratios in excess of 80 
percent unless: (1) the seller retains a participation interest of 10 
percent or more; (2) the seller agrees to repurchase or replace the 
mortgage upon default (seller recourse); or (3) the amount of the 
mortgage in excess of 80 percent is insured or guaranteed.\151\ 
Multifamily mortgages are not subject to such a requirement, but may 
also be credit enhanced.
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    \151\ See sections 305(a)(2) and (4)(C) of the Federal Home Loan 
Mortgage Corporation Act (12 U.S.C. 1454(a)(2) and (4)(C)) and 
sections 302(b) and (5)(C) of the Federal National Mortgage 
Association Charter Act (12 U.S.C. 1717(b)(2) and (4)(C)).
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    The Enterprises currently use several different types of credit 
enhancements: (1) Private mortgage insurance on individual loans, which 
usually covers a percentage of the gross loss, or ``claim amount,'' 
\152\ (2) seller recourse agreements, which require the seller/servicer 
to repurchase loans in the event of default, either for all loan 
defaults (unlimited recourse) or for all defaults up to a specified 
amount (limited recourse); (3) indemnification, which requires the 
seller/servicer to reimburse the Enterprises for losses (either 
unlimited or limited) on defaulted loans after final resolution by the 
Enterprise; (4) pool insurance, which covers losses on a pool of loans 
up to a specified percentage of the aggregate unpaid principal balance 
(UPB), usually after private mortgage insurance has been applied; (5) 
spread accounts maintained by the Enterprise or a custodian to offset 
losses, funded by part of the spread between the interest rate on the 
loans in a pool and the coupon passed through to the investor; (6) 
collateral pledge agreements under which the Enterprise obtains a 
perfected interest in securities held in an account (usually Treasury 
securities or mortgage-backed securities), to offset losses on a pool 
of loans when a seller/servicer hits certain financial triggers or when 
the loans are high risk; and (7) cash accounts funded by the seller/
servicer that are available to offset losses.
---------------------------------------------------------------------------

    \152\ The claim amount includes the defaulted principal balance, 
unpaid interest, and associated expenses. It does not reflect 
subsequent proceeds from the sale of REO.
---------------------------------------------------------------------------

2. Modeling Approach
    The stress test calculates the loss coverage provided by credit 
enhancements in one of two ways, depending on the credit enhancement 
type. Private mortgage insurance, unlimited recourse, unlimited 
indemnification, and risk-sharing agreements provide coverage for a 
percentage of the loss incurred. The dollar value of these credit 
enhancements is not known at the beginning of the stress period because 
it depends on the size of the loss that occurs in the future. What is 
known is the percentage of the loss that will be covered. Therefore, 
these credit enhancement types are referred to herein as ``percent-
denominated'' enhancements. The other credit enhancement types are 
referred to as ``dollar-denominated'' enhancements, because the total 
coverage provided can be expressed in dollar amounts without knowing 
the size of the losses in advance.
    The stress test applies the loss coverage provided by credit 
enhancements to the loan groups into which individual loans have been 
aggregated for modeling efficiency. (See section II. A., Summary of the 
Stress Test, for a description of the characteristics that are the 
basis for aggregation.) The loss coverage is a weighted average of the 
credit enhancements applicable to any loans in the group. In situations 
where a loan group is covered by both percent-denominated enhancements 
and dollar-denominated enhancements, the two different types of credit 
enhancements are applied sequentially. First, the loss severity of a 
loan group is reduced by an amount that is determined by the percentage 
coverage of the applicable percent-denominated credit enhancements. 
Then, the dollar coverage available from dollar-denominated credit 
enhancements is applied to the remaining losses on the loan group until 
all of the available dollar coverage for that loan group is used up. 
This approach permits percent-denominated credit enhancements (such as 
private mortgage insurance) to be applied before dollar-denominated 
credit enhancements (such as pool insurance) are applied, capturing the 
benefits of multi-layered credit enhancements.

[[Page 18151]]

    Some dollar-denominated enhancements provide coverage in a dollar 
amount that is fixed and known at the time the agreement is executed. 
These include pool insurance, limited recourse, limited 
indemnification, and cash accounts. Other dollar-denominated 
enhancements provide coverage in a dollar amount that is subject to 
variation during the term of the agreement. These include spread 
accounts and collateral pledge agreements. Changes in these balances 
due to reasons other than loss coverage are not modeled. Rather, 
balances are treated as cash \153\ and drawn upon after dollar losses 
are determined, until the total amount is exhausted.
---------------------------------------------------------------------------

    \153\ Although dollar balances for these types may in reality 
vary during the stress period, the stress test uses the balance 
stated at the beginning of the stress period.
---------------------------------------------------------------------------

    Some credit enhancements, namely private mortgage insurance, 
recourse, pool insurance, and indemnification, are subject to the 
institutional credit risk of the provider, i.e. the risk that the 
counterparty providing the credit enhancement will default on its 
obligation. Where institutional credit risk is present, the stress test 
applies a discount factor, or ``haircut,'' based on the credit rating 
of the counterparty.
    The haircuts that have been adopted by OFHEO are set forth by 
rating category in Table 27:
[GRAPHIC] [TIFF OMITTED] TP13AP99.212

    The haircuts reflect the probability that some counterparties will 
be unable to meet their obligations during the stress period. Haircuts 
become progressively larger as the counterparty rating decreases, with 
parties rated BBB or lower and unrated parties receiving the most 
severe haircut. The haircut for each rating category is cumulative 
rather than additive. It increases for each month of the stress period, 
beginning in the first month of the stress test and increasing by equal 
amounts (i.e., linearly), until the full amount of the discount is 
reached in the 120th month. Table 27 reflects the size of the haircut 
at the end of each 12-month period during the stress period. Rating 
downgrades are not modeled. Instead, deterioration in the financial 
condition of counterparties due to the stressful environment is 
reflected in the linear increase of the haircuts.
3. Comments and Alternatives Considered
    In the ANPR, OFHEO requested comments on how to calculate the loss 
coverage provided by credit enhancements and on what assumptions to 
make about the scope of coverage and the failure of counterparties 
during the stress period. These and other issues, relevant comments 
received, and OFHEO's rationales for the selected approaches are 
discussed below.
a. Modeling Approach
    ANPR commenters suggested a variety of modeling approaches. MICA 
stated that the capital requirements for the Enterprises should be 
consistent with capital requirements for banks and thrifts and reflect 
the underlying product risk associated with each class of mortgage-
related assets. MICA recommended that OFHEO assign relative ``capital 
relief'' values to ``the three allowable credit enhancements'' \154\ 
based on the quantity and quality of the credit enhancement. MICA 
further recommended that OFHEO consider mortgage insurance provided by 
a company with at least a AA claims-paying rating and providing at 
least the minimum coverage required by the Enterprises' charters as the 
``benchmark credit enhancement.'' The benchmark credit enhancement 
should receive the ``maximum amount of capital relief,'' and other 
forms of credit enhancement should receive values relative to this 
benchmark, based on the quality and quantity (i.e. the amount of the 
loss it covers) of the enhancement. (See section III.C.3.c., 
Discounting for Counterparty Risk for a discussion of MICA's comments 
related to the quality of the credit enhancement.) MICA views this 
approach as consistent with risk-based requirements for banks and 
thrifts, which require uninsured high-LTV

[[Page 18152]]

loans held in portfolio to have twice as much capital as high-LTV loans 
that are privately insured.
---------------------------------------------------------------------------

    \154\ OFHEO interprets ``three allowable credit enhancements'' 
as a reference to the three types of credit enhancement mentioned in 
the Charter Act exception to the prohibition on purchasing loans 
with LTVs in excess of 80 percent.
---------------------------------------------------------------------------

    Freddie Mac suggested a two-step process similar to the process it 
uses in its internal models for pricing transactions. Freddie Mac first 
estimates the value of the credit enhancement by estimating the 
proportion of default losses that would be covered, and then discounts 
the estimated value to reflect the institutional credit risk of the 
provider, if any. Although Freddie Mac`s credit enhancement valuation 
process occurs at the transaction level for pools of mortgages, Freddie 
Mac suggested that such a transaction-level approach might not be well 
suited for OFHEO's stress test. Rather, it recommended aggregating 
credit enhancements into categories before applying the two-step 
process. Freddie Mac further recommended that private mortgage 
insurance be modeled in connection with the modeling of loss 
severities. Other types of credit enhancements, Freddie Mac suggested, 
could be converted to ``collateral-equivalent'' amounts and, after 
discounting for applicable institutional credit risk, aggregated into a 
large collateral-equivalent pool and used to offset stress test losses 
dollar for dollar. Freddie Mac made specific recommendations for 
collateral-equivalent conversions: collateral pledge agreements and 
spread accounts should be included on a dollar-for-dollar basis and 
future inflows to spread accounts should be estimated based on the 
weighted average life (WAL) of the pool; \155\ pool insurance should be 
included to the policy limit, i.e. the percentage limitation multiplied 
by the original UPB; and recourse and indemnification agreements should 
be treated as if 100 percent of the losses from mortgage defaults in 
the applicable pools were covered until such time as the seller/
servicer failed.
---------------------------------------------------------------------------

    \155\ This could be done by multiplying the WAL by the average 
yearly spread going into the spread account and then by the UPB.
---------------------------------------------------------------------------

    The approach adopted by OFHEO is similar in many respects to the 
approach suggested by Freddie Mac. Like Freddie Mac's approach, it 
estimates the probable coverage of credit enhancements and discounts 
for counterparty risk where it is present. The value of private 
mortgage insurance and other forms of credit enhancements that cover a 
percentage of loss is estimated in connection with loss severities, as 
suggested by Freddie Mac. The approach adopted by OFHEO differs from 
the approach suggested by Freddie Mac in some of the details of how 
credit enhancement coverage is estimated and how discounts for 
counterparty risk are calculated. These differences are discussed 
further below.
b. Aggregation
    A threshold issue for OFHEO was whether to track and model each 
credit enhancement with the loan or pool to which it relates or to use 
some level of aggregation for credit enhancements to increase modeling 
efficiency. Tracking and modeling each individual credit enhancement 
agreement with the particular loan or pool to which it is related would 
yield the most precise estimate of the value and behavior of credit 
enhancements, but would make the model very complex. Aggregating credit 
enhancements for efficiency in modeling, on the other hand, gives rise 
to ``cross support,'' which overestimates the amount of credit 
enhancements that would actually be used to offset losses. ``Cross 
support'' means that credit enhancements provided on a particular loan 
or pool are available to offset losses on another loan or pool, when in 
practice they would be available only to offset losses on the 
particular loan or pool for which they were provided and would be 
partially unused if losses were lower than the amount of the coverage. 
However, in a model that aggregates credit enhancements and applies 
them to loan groups, the unused portion of a credit enhancement is 
available to cover losses in the same loan group. The greater the 
aggregation of credit enhancements in the stress test, the more cross 
support occurs, and the more the estimated value of the credit 
enhancements is overstated. Aggregation up to a very high level can 
introduce an unacceptable level of cross support.
    OFHEO considered converting each credit enhancement type to a 
dollar-equivalent amount, aggregating these amounts across all credit 
enhancement types into a single pool of collateral-equivalent dollars, 
and applying them dollar for dollar against stress test losses. While 
this approach is simpler and would have required less intensive 
tracking, it would permit an unacceptable level of cross-support by 
credit enhancements of different types and for different loan groups. 
Just as importantly, this approach would not have produced accurate 
results for the coverage associated with percent-denominated credit 
enhancements, such as private mortgage insurance. The dollar amount of 
coverage of these credit enhancements cannot be calculated until losses 
are determined. These losses can only be calculated during the course 
of the stress period; they are not known at the beginning of the stress 
period.
    The approach adopted by OFHEO strikes a balance between the 
benefits of simplicity and efficiency and the benefits of precision 
while imposing minimal regulatory burden. By estimating the coverage 
provided by each type of credit enhancement on the basis of loan 
groups, tracking credit enhancements for each loan group can be 
accomplished efficiently. The large number of loan groups used by the 
stress test minimizes cross support between different types of credit 
enhancements, loans, and time periods.
c. Discounting for Counterparty Risk
    Another issue faced by OFHEO was whether and how to take into 
account the risk that the counterparty's ability to perform on the 
credit enhancement agreement would be affected by the conditions of the 
stress test.
    OFHEO received a number of suggestions on the treatment of 
counterparty risk in response to the ANPR. Freddie Mac, MICA, and ACB 
recommended incorporating an assumption that some of the counterparties 
would fail during the stress period and suggested that OFHEO look to 
private rating agencies for guidance. ACB suggested that the OFHEO 
analysis of the actual coverage provided by mortgage insurance during 
the stress period could be ``piggybacked'' on S&P's analysis. ACB 
further stated that OFHEO could make reasonable adjustments to align 
the worst-case scenario in S&P's stress test with that in the OFHEO 
analysis, and that it would not be necessary to extend the analysis 
beyond private mortgage insurers.
    As noted earlier, MICA recommended a matrix for determining 
``capital relief'' for credit enhancements relative to a benchmark 
credit enhancement. One dimension of the recommended matrix is the 
credit rating of the counterparty, reflecting an assumption that the 
values assigned to various credit enhancements should reflect a 
differentiation on the basis of the provider's claims-paying rating. 
However, MICA's recommendation that OFHEO give ``maximum capital 
relief'' (at least 50 percent of the normal capital charge) to a AA-
rated insurer providing at least the minimum coverage required by the 
Enterprises' charters appears to be equivalent to a recommendation that 
AA-rated counterparties not be discounted at all.\156\ MICA asserted 
that

[[Page 18153]]

this recommendation is supported by the historical default experience 
for corporate bonds in the 1970-89 period, particularly the 0.9 percent 
default rate for AA-rated bonds.\157\ From this MICA concluded that 
99.1 percent of mortgage insurance would be available to the 
Enterprises during the stress period.
---------------------------------------------------------------------------

    \156\ The risk-based capital requirements for banks and thrifts 
are not determined by a statutorily prescribed stress test but by 
establishing a standard capital charge for all assets that is 
expressed as a fixed percentage of the face amount of the asset. 
Capital relief for particular assets is achieved by risk weighting 
them at less than 100 percent of the face amount. Risk-based capital 
regulations for banks and thrifts risk-weight mortgage loans at 50 
percent of the UPB. In a stress test regulation, the most favorable 
capital treatment is achieved by giving full credit for the credit 
enhancement without any discount.
    \157\ ``Approach to Rating Residential Mortgage Securities,'' 
Moody's Investor Service, April 1990.
---------------------------------------------------------------------------

    Freddie Mac recommended that evaluation of counterparty risk be 
based on the probable length of time an institution would continue 
meeting its loss-paying obligations in the stress period, which would 
be determined by the institution's rating at the beginning of the 
stress period. This method, Freddie Mac asserted, is similar to one 
used by Moody's. Specifically, AAA-rated companies would be assumed to 
cover all obligations for the entire ten-year stress period. AA-rated 
companies would be assumed to cover all obligations for seven years and 
none thereafter, A-rated companies for five years, and companies rated 
BBB and lower, only three years. Freddie Mac also recommended that 
institutions that are required to post collateral under a collateral 
pledge agreement be ranked with AAA-rated institutions. For recourse 
and indemnification agreements, Freddie Mac suggested that OFHEO could 
assume the agreement would last until the institution failed, a time 
determined by the institution's rating. It noted, however, that a 
similar effect could be achieved by adjusting the loss severities based 
on institution ratings, where the adjustment to loss severity would be 
lower for a higher institutional rating. However, Freddie Mac cautioned 
that if this approach were used, the difference between the present-
value cost of losses occurring at the end of the stress period and 
losses occurring at the beginning of the stress period would have to be 
taken into account. That is, an institution that honors its recourse 
agreement for the first five years of the ten-year stress period would 
pay out much more than half of the present value of the losses.
    Only one commenter suggested that credit enhancements having 
counterparty credit risk not be discounted for the risk. The MBA 
expressed concern about the burden it would place on the Enterprises to 
determine the financial strength of third parties and suggested that 
credit enhancements need not and should not be discounted for credit 
risk of the counterparty. The reasons cited were three. First, the 
Enterprises generally accept credit enhancements only from well-
capitalized companies. Moreover, the Enterprises are in a good position 
to evaluate the counterparty's financial strength,\158\ and the seller/
servicer agreement often provides added protection from default on 
repurchase or indemnification obligations. Second, an assessment of 
counterparty credit risk is reflected in guarantee fees, which can be 
adjusted with each commitment. And third, mortgage insurers are 
nationally rated by recognized organizations that routinely adjust 
ratings based on changes in financial status. As a result, trends in 
their financial health can be monitored easily. The MBA urged OFHEO to 
ground its assumptions and conclusions in historical experience and 
``real world'' conditions, which, in its view, argue for not 
discounting credit enhancements for counterparty risk.
---------------------------------------------------------------------------

    \158\ This results, MBA noted, from close relationships between 
the Enterprises and seller/servicers based on frequent marketing 
contacts, Enterprise auditing activities, and lender reporting 
obligations.
---------------------------------------------------------------------------

    OFHEO believes that some counterparty failure would be likely under 
the stressful conditions imposed by the stress test and that 
discounting for counterparty credit risk is necessary to avoid 
overstating the effect of credit enhancements in covering losses. The 
statutorily required benchmark stress period is considerably more 
severe than the national historical experience of corporate bonds cited 
by MICA. Also, as noted by Anthony Yezer, Professor of Economics at 
George Washington University, the failure of private mortgage insurers 
was important in the collapse of the thrifts in the 1930s.
    Although the stress test reflects assumptions about the claims-
paying abilities of counterparties during the stress period that are 
similar to Freddie Mac's, OFHEO did not adopt Freddie Mac's assumption 
that counterparties would pay 100 percent of their obligations as long 
as they paid at all. In OFHEO's judgment, this assumption is 
inconsistent with the pattern of counterparty defaults on obligations 
that one would expect during a stressful period and inconsistent with 
the pattern of defaults observed in the past. For example, Moody's 
study of corporate bond defaults \159\ showed that cumulative defaults 
in each of the various ratings categories increased gradually over 
time. Also, it is likely that the primary market and credit enhancement 
counterparties would be affected by the stress test conditions 
relatively early in the stress period. Freddie Mac's approach would not 
capture this early impact. If mortgage losses were to occur during the 
first half of the stress period, the importance of reductions in credit 
enhancements due to counterparty risk would be understated because, as 
noted by Freddie Mac, mortgage losses occurring during the first half 
of the stress period constitute much more than half of the present 
value of total losses. Therefore, credit enhancements offsetting those 
losses would be more valuable. A more realistic assumption is that the 
rate of counterparty defaults would increase gradually during the 
stress period.
---------------------------------------------------------------------------

    \159\ ``Historical Default Rates of Corporate Bond Issuers, 
1920-1997,'' Moody's Investors Service, February 1998.
---------------------------------------------------------------------------

    OFHEO did not adopt Freddie Mac's recommendation to treat seller/
servicers who are required to post collateral when certain financial 
triggers are met \160\ the same as AAA-rated institutions. Freddie Mac 
contends that the existence of these agreements would provide coverage 
equivalent to a AAA-rated credit enhancement. However, whether 
collateral would actually be posted when required is an additional 
source of counterparty risk and whether that collateral would provide 
coverage equivalent to a AAA-rated credit enhancement is difficult to 
evaluate in a regulatory context. Such an evaluation would require 
OFHEO either to develop the capacity to rate each seller/servicer with 
a collateral pledge agreement and the impact of the agreement on the 
seller/servicer's rating, or to require the Enterprises to obtain 
public ratings for such seller/servicers that take these agreements 
into account. In light of the small impact that this degree of 
precision is likely to have on the capital requirement, OFHEO believes 
that developing such a rating capacity is not an appropriate use of 
regulatory resources, and that requiring the Enterprises to obtain 
public ratings would impose an undue regulatory burden. Consequently, 
the proposed stress test does not model the value of collateral pledge 
agreements. Instead, it only models coverage provided by collateral 
that is already available in an Enterprise or third-party account.
---------------------------------------------------------------------------

    \160\ Seller/servicer agreements may include such a requirement 
when there is a decline in the institution's rating or a decline in 
its capital levels below a specified amount.
---------------------------------------------------------------------------

    This treatment is consistent with the treatment of such agreements 
under OFHEO's minimum capital regulation. Collateral is not recognized 
for purposes

[[Page 18154]]

of satisfying the minimum capital standard unless it is actually held 
and legally available to absorb losses. Also, to be consistent with the 
minimum capital restrictions on the forms of collateral that are 
acceptable, the proposed stress test will give credit for the coverage 
provided by collateral only if it is among the following types: cash on 
deposit; securities issued or guaranteed by the central governments of 
the OECD-based group of countries,\161\ United States Government 
agencies, or United States Government-sponsored agencies, and 
securities issued by multilateral lending institutions or regional 
developments banks.
---------------------------------------------------------------------------

    \161\ The OECD-based group of countries comprises all full 
members of the Organization for Economic Cooperation and Development 
and countries that have concluded special lending arrangements with 
the International Monetary Fund (IMF) associated with the IMF's 
General Arrangements to Borrow, but excludes any country that has 
rescheduled its external sovereign debt within the previous five 
years.
---------------------------------------------------------------------------

    In determining the size and timing of the discounts (haircuts) to 
the value of the credit enhancements, OFHEO considered Moody's study of 
corporate bond default rates and methodologies used by S&P and Duff & 
Phelps (D&P). Moody's analysis of corporate bond issuers from 1920 to 
1997 \162\ showed cumulative default rates over various time horizons 
for each rating category. The average ten-year cumulative default rate 
over the entire period was 1.17 percent for Aaa issuers, 3.32 percent 
for Aa issuers, 3.87 percent for A issuers, 8.08 percent for Baa 
issuers. These data suggest that the ten-year cumulative default rate 
roughly doubles for each one-level drop in rating category. Defaults 
for Aa issuers were higher relative to those for Aaa and A issuers than 
this doubling relationship would suggest. However, Aa issuers from the 
mid-1970s forward had ten-year cumulative default rates that were much 
lower relative to issuers in other rating categories.
---------------------------------------------------------------------------

    \162\ ``Historical Default Rates of Corporate Bond Issuers, 
1920-1997,'' Moody's Investors Service, February 1998.
---------------------------------------------------------------------------

    The Moody's approach and the approach recommended by Freddie Mac is 
a survival approach in which it is assumed that an institution meets 
100 percent of its obligations for as long as it survives, and relative 
risk is expressed as the number of years an institution survives. The 
approach used by S&P and D&P \163\ is a haircut approach in which it is 
assumed that institutions will meet some, but not all, of their 
obligations, and the haircut is the percent of obligations they will 
fail to meet. Specifically, S&P discounts the claims-paying ability of 
mortgage insurers in a AA stress level environment by 20 percent for 
AA-minus-rated mortgage insurers, 50 percent for A-rated mortgage 
insurers, and 60 percent for A-minus-rated mortgage insurers. D&P 
discounts mortgage insurers in a AAA stress level environment by 35 
percent for AA-rated reinsurers, 70 percent for A-rated reinsurers, and 
100 percent for BBB-rated reinsurers. For S&P, the haircuts apply in 
full from the second year of the stress period. Also, the haircut is 
related to the stress level of the environment, and an insurer with a 
rating equal to or greater than the stress level is not discounted.
---------------------------------------------------------------------------

    \163\ ``S&P's Structured Finance Criteria,'' Standard & Poor's 
Corporation, 1988; ``Evaluation of Mortgage Insurance Companies,'' 
Duff & Phelps, November, 1994.
---------------------------------------------------------------------------

    Moody's corporate bond study shows that the cumulative default 
curves for companies with ratings of BBB and above were essentially 
linear.
[GRAPHIC] [TIFF OMITTED] TP13AP99.370

    OFHEO's approach to applying haircuts is similar to S&P's and 
D&P's, but differs in three ways. First, the stress test does not apply 
the full amount of the haircut immediately but applies a haircut that 
increases each month until reaching the full amount in the 120th month. 
This reflects the general industry view that defaults increase 
gradually in a stress scenario. Further, as illustrated by the graph in 
Figure 2, the linear growth specification of the stress test is a 
reasonable one in light of actual historical patterns of default. 
Second, the stress test haircuts are in no case as low as zero and in 
no case as high as 100 percent. This reflects historical default 
patterns, which suggest that counterparties or issuers in each rating 
category would pay at least some claims, and no rating category would 
be immune from any claims-paying defaults. With respect to the absence 
of a rating category with zero defaults, Moody's data show that, in a 
difficult but far from severe environment, 3.2 percent of issuers

[[Page 18155]]

rated Aaa at the beginning of 1983 defaulted within 10 years. Third, 
the stress test haircuts are not tied to the stress level. While 
OFHEO's NPR 1 showed credit stress at roughly a AA+ level, the stress 
test as a whole does not translate to any particular level because 
OFHEO's methodology as required by the 1992 Act differs in several key 
respects from that used by rating agencies.
    Although OFHEO considered developing a probabilistic survival 
function for counterparties that would provide an estimate of failure 
in each year of the stress period, such a methodology would be 
difficult to specify, implement, and replicate, especially if recovery 
rates on bankrupt counterparties were modeled. OFHEO concluded that, 
short of a probabilistic function, imposing a linearly increasing 
haircut on all counterparty credit enhancement proceeds through the 
entire stress period would be the most representative of all the other 
options of how the rate of counterparty defaults would increase during 
the ten-year stress period.
    The size of the haircuts proposed for the stress test, ten percent 
for AAA-rated companies, 20 percent for AA-rated companies, 40 percent 
for A-rated companies, and 80 percent for BBB-rated companies, are far 
more severe than recent default experience but less severe than 
Depression-era experience. They are about six to ten times the severity 
of average ten-year cumulative defaults during 1920-1997 in the Moody's 
analysis. The haircuts double for each drop in rating category, 
consistent with the Moody's bond default analysis. Some default occurs 
among AAA-rated companies, while BBB-rated company defaults are not 100 
percent.
    OFHEO's approach is transparent, easily replicated, and consistent 
with industry practice. It draws on the best aspects of S&P's approach 
to modeling mortgage insurer performance, and Moody's corporate bond 
study in applying company defaults over time. It also recognizes that, 
while the impact of the stress test environment on Enterprise losses 
might not be large in the first two years of the stress period, the 
primary mortgage market (i.e., the seller/servicer counterparties) 
likely would feel the impact of a stressful environment almost 
immediately.
d. Unrated Seller/Servicers
    OFHEO considered whether unrated seller/servicers should be treated 
the same as other unrated counterparties or whether they should be 
treated differently because of their close relationships with the 
Enterprises.
    Both Freddie Mac and MBA argued that even though seller/servicers 
are typically unrated, the close relationship between the Enterprise 
and its seller/servicers enables the Enterprise to monitor their 
financial strength. Freddie Mac stated that the seller/servicer 
agreement provides added protection against default on recourse and 
indemnification obligations because it gives Freddie Mac the right to 
the servicing of all Freddie Mac loans then serviced by the institution 
in the event of default on these obligations. Freddie Mac asserted that 
the value of the servicing is likely to cover a substantial portion of 
the defaults covered by a seller/servicer recourse agreement.\164\ For 
these reasons, Freddie Mac considers all sellers/servicers to be at 
least BBB for purposes of evaluating institutional credit risk and 
urged OFHEO to consider the added layers of protection provided by the 
servicing rights.
---------------------------------------------------------------------------

    \164\ Freddie Mac estimates that these servicing rights are 
normally worth about 25 basis points of income per year, and can be 
sold to another servicer for 100 to 150 basis points.
---------------------------------------------------------------------------

    The stress test treats unrated seller/servicers, like other unrated 
counterparties, the same as it treats BBB counterparties, which is 
consistent with the thrust of Freddie Mac's ANPR comments. Although 
OFHEO does not explicitly price the added layer of protection provided 
by mortgage servicing rights in its stress test, this added layer of 
protection was considered as a factor in deciding that unrated 
counterparties should be treated as BBB. OFHEO believes that any 
imprecision resulting from assigning unrated seller/servicers to the 
BBB or lower rating group would have a small impact on the resulting 
capital requirement. Seller/servicer recourse represents a small 
percentage of the credit enhancements used by the Enterprises. In 
addition, the Enterprises' largest customers tend to have public 
ratings.
    Although the Enterprises assign internal ratings to seller/
servicers, OFHEO did not use these ratings for three reasons. First, 
these ratings and the methodology for developing the rating are 
proprietary information and not publicly available. Therefore, they 
cannot be included in the regulation or used by third parties to 
evaluate the risk-based capital requirement. Second, each of the 
Enterprises has developed its own unique rating system. These rating 
systems may result in different ratings of the same parties. One of the 
underlying requirements of this regulation is the development of a 
capital requirement that is applied uniformly to both Enterprises. This 
requirement cannot be met if different rating systems are applied to 
each Enterprise. Finally, using such ratings without independent 
validation by OFHEO would compromise the independence of the regulatory 
process.
e. Fluctuations in Value
    The dollar value of some credit enhancements, such as spread 
accounts and securities deposited in an account under collateral pledge 
agreements, fluctuate over time, for reasons other than withdrawals to 
cover losses. Spread accounts are funded by a portion of each loan 
payment and hence increase in value as loan payments are made. 
Securities deposited in an account under collateral pledge 
agreements,\165\ which are marked to market periodically, fluctuate in 
value due to movements in interest rates during periods that fall in 
between the marks to market. In addition, posting requirements of 
collateral pledge agreements can cause additional collateral to be 
deposited to the account.
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    \165\ As stated earlier, the stress test recognized the coverage 
provided by collateral pledge agreements only if collateral has 
actually been posted and resides in an account as of the beginning 
of the stress period. Otherwise, collateral pledge agreements are 
not modeled in the stress test.
---------------------------------------------------------------------------

    The stress test does not model these fluctuations. Rather, it uses 
the dollar value of spread accounts, cash accounts, and collateral 
posted under collateral pledge agreements on the first day of the 
stress period and draws on this dollar amount throughout the stress 
period to cover losses. Modeling fluctuations in the value of 
collateral posted under collateral pledge agreements would have added a 
level of complexity that is not justified by the incremental precision 
that would be gained. Similarly, the stress test does not model the 
accumulation of interest in the spread account according to the terms 
of the spread account agreement because this would have introduced a 
level of complexity that is not justified by the probable impact on the 
ultimate capital requirement.
    Freddie Mac suggested that OFHEO estimate future inflows by 
multiplying the weighted average life (WAL) of the mortgage pools by 
the average yearly spread going into the spread account and then by the 
UPB. However, such an approach would also have made the stress test 
excessively complex. Loans covered by a spread account agreement may be 
in different loan groups in the stress test, and determining the WAL of

[[Page 18156]]

all the loans covered by each spread account would require tracking 
each spread account loan and processing spread account characteristics 
at the transaction level.
    OFHEO will continue to monitor the relative volume of spread 
accounts and collateral pledge agreements and consider whether an 
amendment to the regulation is needed if it should appear that the 
impact on the capital requirement might be significant.
f. Credit Enhancement on High LTV Loans
    Certain credit enhancement types used by the Enterprises are not 
mentioned in the Charter Acts' exceptions to the prohibition on 
purchasing single family loans with LTVs in excess of 80 percent, 
namely spread accounts, collateral pledge agreements, cash accounts, 
pool insurance, and indemnification. This fact raised the issue of 
whether the stress test should take them into account when they are 
intended to satisfy the statutory requirement for credit enhancement on 
loans with LTVs in excess of 80 percent. In its comment letter, Freddie 
Mac argued that an expansion of the list of recognized credit 
enhancements to include collateral pledge agreements, spread accounts, 
and indemnification would be consistent with the intent of Congress in 
giving the OFHEO Director discretion to make reasonable assumptions 
about factors that would affect the severities of loss on mortgage 
defaults, including ``the value of mortgage insurance [and] the value 
of various forms of credit enhancements such as recourse agreements, 
collateral, and spread accounts.'' \166\ MICA, on the other hand, 
argued that only the three types mentioned in the statutory exceptions 
should be considered.
---------------------------------------------------------------------------

    \166\ H.R. Rep. No.102-206, at 67 (1991).
---------------------------------------------------------------------------

    Although OFHEO recognizes that some types of credit enhancements 
not expressly referenced in the Charter Acts may provide equal or 
superior loss protection, OFHEO does not believe that they satisfy the 
statutory requirement for credit enhancements for single family loans 
with LTVs in excess of 80 percent. OFHEO does not concur with Freddie 
Mac that the legislative history of the 1992 Act gives OFHEO the 
latitude to expand the list of statutorily authorized credit 
enhancements for single family loans with LTVs in excess of 80 percent. 
OFHEO believes that taking into account credit enhancements not 
expressly referenced in the Charter Acts when they are used to satisfy 
the statutory credit enhancement requirement for single family loans 
with LTVs in excess of 80 percent would undermine OFHEO's efforts to 
ensure that the Enterprises operate within the Charter Acts.
g. Scope of Coverage
    The ANPR asked for comments on how the regulation should address 
the scope of coverage provided by credit enhancements. Freddie Mac, the 
only commenter on this question, stated that all credit enhancements 
except private mortgage insurance can be assumed to cover all loss 
elements, including loss of property value, lost interest, real estate 
commissions, attorney fees, taxes, and preservation costs, where as 
private mortgage insurance sometimes excludes certain expenses after 
the property becomes REO.
    Based on an analysis of available information, OFHEO proposes to 
make credit enhancements coverage available for all types of losses 
associated with stress test defaults. The benchmark data reveal that 
loss severities before credit enhancements were applied for single 
family loans in the benchmark time and place were consistently in the 
50 percent to 60 percent range. At the same time, private mortgage 
insurance coverage typically ranged from 12 percent to 30 percent 
coverage of the gross claim amount. Since the severities far exceed the 
coverage of private mortgage insurance, the stress test assumes that 
the private mortgage insurance would be used up covering expenses that 
the mortgage insurance typically covers, and that the REO-related 
expenses would be reflected in the uncovered losses.
h. Termination of Private Mortgage Insurance
    Modeling private mortgage insurance required a determination of how 
to treat the potential for termination of mortgage insurance while the 
loan is outstanding. Termination occurs either because the borrower 
exercises an option to cancel the insurance when the equity in the loan 
reaches a predetermined threshold, or because cancellation is automatic 
under the provisions of the recently enacted Homeowners Protection Act 
of 1998.\167\ For loans originated before the July 1999 effective date 
of the Homeowners Protection Act, termination resulting from the 
borrower's exercise of the right to cancel the insurance when 
sufficient equity in the loan is attained presents a difficult issue, 
because data on this phenomenon are scarce, and there is an 
insufficient basis on which to draw firm conclusions. OFHEO considered 
three options: (1) assume that borrowers do not exercise this right 
when they are eligible; (2) assume all borrowers exercise this option 
when they become eligible; or (3) assume some percentage of borrowers, 
less than 100 percent, exercise this option when they become eligible.
---------------------------------------------------------------------------

    \167\ Pub. L. No.105-216, 112 Stat. 897-910 (12 U.S.C. 4901-
4910).
---------------------------------------------------------------------------

    After considering these options, OFHEO concluded that the first 
option was the preferred option because it is the option likely to 
produce the least distortion. The second option would understate the 
amount of credit enhancement available and the third would require an 
assumption based on very sparse data. Although assuming that insurance 
is not terminated may be a source of some imprecision, the impact of 
such imprecision is not likely to be significant in determining capital 
needed under the stress test. The loans most likely to default are 
those loans with high current LTV ratios, which will not be eligible 
for termination of private mortgage insurance because of the high LTVs. 
Conversely, those loans with low enough current LTV ratios to be 
eligible for termination are much less likely to need the coverage, and 
whether it is unused or is assumed to be terminated will make little 
difference. The largest potential for error is with loans with high 
original LTV ratios that have aged prior to the stress test just to a 
point where coverage can be terminated. OFHEO will monitor this issue 
and consider proposing an amendment to the regulation if another option 
appears to be more appropriate.
    The Homeowners Protection Act provides that mortgage insurance will 
terminate automatically when the loan balance is scheduled to reach 78 
percent of the original value of the property securing the loan, 
provided payments on the loans are current. For loans that do not meet 
the LTV test and for high-risk loans with original principal balances 
that do not exceed the conforming loan limit, mortgage insurance will 
terminate when the loans reach the mid-point of their amortization 
periods if payments are current. The Enterprises will publish 
guidelines to describe high-risk loans. OFHEO proposes to apply the 
provisions of the Act by eliminating mortgage insurance coverage in 
calculating loss severities for loans that reach 78 percent of their 
original value during the stress period or at the midpoint of their 
amortization periods for ``high risk'' loans, as defined by the 
Enterprises.

[[Page 18157]]

D. Liabilities and Derivatives

    The Enterprises issue a variety of debt instruments that comprise 
their liability portfolios. To understand the types of liabilities 
issued by the Enterprises it is useful to group the liabilities into 
categories based on similar characteristics related to the instrument's 
coupon type, optionality, or other structuring features. The 
liabilities issued by the Enterprises are primarily one of three coupon 
types: fixed-rate, floating-rate, or zero-coupon. The Enterprises use 
these different types of coupons to manage both their exposure to 
interest rate risk and their cost of funding. The optionality of a 
financial instrument refers to whether that instrument contains an 
embedded option--in the case of the Enterprises liabilities, generally 
a call option. The embedded call option gives the Enterprises the 
opportunity to pay off (call) the debt, at a time prior to its 
contractual maturity. The Enterprises issue a mix of callable and non-
callable (bullet) debt in order to manage their exposure to the 
prepayment risk inherent in their retained mortgage and mortgage 
security portfolios.
    The Enterprises also issue liabilities that have unique structuring 
features, such as complex principal, coupon, or optionality 
characteristics. An example of a complex liability is a Euro discount 
note. To the extent that these notes are issued in foreign currencies, 
the Enterprises are exposed to foreign exchange risk, which is offset 
with hedging transactions at the time the discount notes are issued. An 
example of a liability with complex coupon characteristics is an 
inverse floater. For example, this instrument may pay a fixed rate of 
interest for a given period of time and then revert to an interest 
payment based on the formula 12 percent less six month LIBOR. In this 
case, the Enterprises incur higher interest costs as LIBOR decreases. 
In most situations, the complex risk characteristics of these 
liabilities are hedged at the time of issuance, leaving the Enterprise 
with synthetic ``plain vanilla'' liabilities, which have the coupon and 
option features of a more typical Enterprise liability. These 
liabilities generally are used by the Enterprises to obtain funds at a 
lower net cost than could be obtained by issuing simpler forms of debt.
    In addition to the types of liabilities discussed above, the 
Enterprises also provide investment vehicles, termed Guaranteed 
Investment Contracts (GICs), to various institutions that have specific 
cash flow requirements or need flexibility in making cash withdrawals. 
They comprise a very small percentage of the Enterprises' liabilities. 
GICs can pay or accrue interest. Their principal balances can increase, 
decrease or remain the same.
    The Enterprises, like most large financial institutions, use 
derivatives to help manage the interest rate risk of their assets and 
liabilities. The term ``derivatives'' covers a broad range of 
instruments, the value of which is based on or linked to (i.e., 
``derived'' from) another instrument or a financial market such as 
stocks, interest rates or currencies. A common derivative is an 
interest rate swap, which derives its value from the changes in value 
of interest rates paid on various types of debt instruments. 
Derivatives can be used to hedge the unusual or complex risk 
characteristics of individual debt instruments, such as the complex 
structured liabilities described above. They also can be used to 
rebalance the interest rate risk of an entire portfolio. In short, 
derivatives, like most financial instruments, can either add or reduce 
various types of risk. The risk-based capital regulation, therefore, 
must account for derivatives in order to reflect accurately the risk 
profile of the Enterprises.
    In developing an approach for modeling the cash flows of the 
Enterprises' liabilities and derivatives, OFHEO had to address four 
issues discussed below: (1) should liabilities and derivatives be 
modeled at the instrument level or should they be aggregated in some 
manner; (2) how should instruments linked to foreign currencies or 
unusual risk factors be modeled; (3) how should callable debt and 
cancellable derivatives be modeled; and (4) how should the stress test 
account for the risk of derivative counterparty defaults?
1. Modeling Methodology
    The first issue for OFHEO was whether to model liability and 
derivative cash flows at the instrument level or to aggregate 
individual instruments with similar terms and risk characteristics and 
model the aggregated cash flows based upon average maturities, coupons, 
options, and other features. In response to an ANPR question about how 
OFHEO should simulate gains and losses on derivative activities, 
Freddie Mac suggested that the underlying instruments should be 
modeled. Likewise, Freddie Mac's discussion of liabilities in its 
comments assumes that most liability instruments will be modeled 
individually. The only other comment was ACB's suggestion regarding 
accounting for the risk of counterparty default. ACB's recommendation 
that the stress test ``haircut'' (meaning reduce by a percentage) 
derivative positions when they were ``in the money'' (meaning the 
derivatives have a net positive value to the Enterprises) would require 
modeling cash flows of derivatives individually.
    The issue of modeling liabilities and derivatives on an aggregated 
versus instrument level usually requires a trade-off between accuracy, 
model complexity, and information system resources. In most cases, the 
model for generating cash flows uses the same types of information for 
an individual instrument as it would for a group of similar 
instruments. For this reason, OFHEO's information system resources are 
capable of processing the large number of individual liabilities and 
derivatives in a reasonable amount of time. Therefore, OFHEO proposes 
to model the cash flows of all existing types of liabilities and 
derivatives individually, except certain instruments that have terms or 
risk characteristics based on a foreign currency, which are discussed 
below as a separate issue.
    As with most other liabilities, the stress test will model GICs 
individually. However, given the variety of their terms and purposes, 
it was necessary to simplify the cash flow model for these instruments. 
The stress test models each GIC as if it pays out its specified 
interest on the starting balance amount over the entire stress period, 
unless the GIC includes an explicit maturity date. In the latter case, 
the stress test pays interest only until the maturity date, at which 
point it pays out the total principal.
2. Foreign Currency Linked or Unusual Instruments
    The second liabilities-related issue arises because, from time to 
time, the Enterprises issue foreign currency-denominated debt and 
structured notes that are linked to a foreign currency. As discussed 
above, the Enterprises currently hedge all foreign currency-linked 
securities with derivatives or other financial instruments, resulting 
in synthetic securities denominated in U.S. dollars. Freddie Mac, the 
only ANPR commenter to address this issue, recommends modeling foreign 
currency-linked transactions differently from other instruments, 
explaining that ``hedge cash flows or the netted cash flows need to be 
calculated * * *.''
    OFHEO agrees that currency-linked securities and the associated 
hedging instruments are different from other types of liabilities and 
derivatives of the Enterprises in that the cash flows of the individual 
instruments are linked to changes in currency values. OFHEO also

[[Page 18158]]

recognizes that, in current practice, the Enterprises issue a limited 
volume of currency-linked instruments and transfer all currency risk to 
third parties by hedging instruments. Further, with the exception of 
debt linked to foreign currency, the Enterprises have not issued 
liability instruments that were linked to indices or values (such as 
commodities or stock prices) that are not projected in the stress 
test.\168\
---------------------------------------------------------------------------

    \168\ However, wherever the terms ``foreign currency'' or 
``currency'' are used, they should be read to include any unit or 
value, except those interest rate indices that are included in the 
stress test, in which debt or derivatives may be denominated or to 
which such instruments may be linked.
---------------------------------------------------------------------------

    OFHEO concurs with Freddie Mac's comments that where all the 
currency risk is hedged, by swapping the foreign currency payments into 
dollars, the stress test could calculate the cash flows by creating a 
single synthetic liability, denominated in dollars and paying the net 
amount due under the related transactions. The stress test, therefore, 
applies that approach to instruments that are fully hedged. However, in 
the event that OFHEO finds that the foreign currency risk on any 
liability or derivative instrument has not been transferred fully to a 
third party, the stress test models the cash flow on such instruments 
as follows.
    The stress test creates significant losses in unhedged currency 
positions in both the up-rate and down-rate scenarios. In the up-rate 
scenario, the stress test applies an exchange rate that increases the 
value of the foreign currency against the dollar by the same percentage 
that interest rates increase. For example, if the ten-year CMT shifts 
up by 50 percent, then the foreign currency value is shifted up by 50 
percent against the dollar for the up-rate scenario.\169\ The effect in 
this example would be that the Enterprise would be paying 50 percent 
more dollars due to the unhedged exchange rate shift.
---------------------------------------------------------------------------

    \169\ Shifting the value of the other currency up 50 percent has 
effect of decreasing the value of the dollar against that currency 
by \1/3\. In other words, one could buy the same amount of dollars 
with only \2/3\ the amount of other currency.
---------------------------------------------------------------------------

    A different adjustment is applied in the down-rate scenario. In 
that case, the stress test decreases the exchange rate of the dollar 
proportionately with the decline in the ten-year CMT, creating a 
decrease in the value of the dollar similar to that in the up-rate 
scenario. Thus, a downward shift in the ten-year CMT of 50 percent 
would be associated with a shift down of 50 percent in the exchange 
rate of the dollar. The effect in this example is that the Enterprise 
would be paying twice as many dollars due to the unhedged exchange rate 
shift.
    This approach is simple, conservative and reasonable. The stress 
test recognizes that there can be substantial risk associated with 
unhedged positions in foreign currencies or other indexes or values to 
which instruments can be linked, but that it would be impractical for 
OFHEO to develop indexes for foreign currencies and all other values to 
which liabilities or derivatives could be linked. The exchange rate in 
the up-rate scenario is not based upon a model or an economic 
prediction, but does reflect a recognition that there have been 
occasions in the past where the dollar has declined in value as CMT 
rates have been increasing. Likewise, the dollar has also declined at 
times when CMT rates have decreased. Therefore, it is appropriate in a 
stress test to assume that the dollar moves in an unfavorable direction 
in both scenarios, to avoid creating a windfall to the Enterprises and 
to ensure significant financial stress in both scenarios. Moreover, 
OFHEO does not anticipate at this time that the Enterprises will be 
issuing foreign currency or unusual debt derivatives without using 
appropriate and complete hedges. If the Enterprises do alter their 
current businesses to enter into such debt, OFHEO will consider at that 
time whether a different treatment for the instruments involved is 
appropriate.
3. Call and Cancellation Options
    An Enterprise will retire an outstanding issue of callable debt in 
order to issue new debt at favorable rates. For similar reasons an 
Enterprise may cancel a swap. For example, an Enterprise can cancel a 
pay-fixed/receive-floating swap--which, together with discount notes, 
creates a synthetic fixed-rate liability--in order to enter into a new 
swap that lowers the effective cost of the synthetic liability. OFHEO 
recognizes that, in general, an Enterprise will exercise its option 
when the net interest cost savings on a replacement security or 
contract, exceeds some threshold.
    OFHEO received several comments to the ANPR that emphasized the 
importance of modeling the exercise of the call option. OFHEO concurs 
with these comments and, accordingly, treats callable debt in a manner 
that takes into consideration the exercise of the call option. OFHEO 
considered developing a financial model to value call and cancellation 
options and determine when they would be exercised in the stress test. 
However, the added precision of such a valuation model, as opposed to a 
simpler approach, would not have a significant effect on the capital 
requirement because the severe nature of the interest rate shocks 
included in the stress test result in either all eligible debt being 
called in a short period of time or no debt being called over the 
entire period. In addition, a valuation model would add a considerable 
amount of complexity to the cash flow model. Therefore, OFHEO sought to 
develop an alternative approach for decisions to exercise call and 
cancellation options that would provide a reasonable approximation of 
the Enterprises' procedures for exercising such options without 
increasing the complexity of the model.
    OFHEO proposes to use, as a proxy for this threshold option value, 
the spread between the coupon rate of an outstanding actual or 
synthetic debt security and the Enterprise cost of funds for a new 
replacement security (the call-spread). Thus, in the stress test, the 
call option is exercised and the debt retired when the cost of the new 
debt plus the call-spread is less than the cost of the existing debt 
instrument. This methodology is often used as a simplified approach in 
modeling applications and was suggested by Freddie Mac in its comments 
to the ANPR. No other commenter suggested a specific approach.
    To calculate an appropriate call spread, OFHEO received data from 
the Enterprises on the threshold value of call options on debt, in 
terms of a call-spread, over a range of reasonable times to maturity 
and valuation model parameter settings. After reviewing this 
information, OFHEO proposes to use a call-spread in the stress test of 
50 basis points over the cost of issuing new bullet debt with the same 
time to maturity as the callable debt. This call-spread provides a 
reasonable debt call rule, without adding a considerable amount of 
complexity to the model.
4. Counterparty Risk
    The ANPR sought comment about how, if at all, OFHEO should 
incorporate the effect of derivative counterparty defaults into the 
stress test. The Enterprises frequently enter into derivative contracts 
that, combined with various types of debt instruments (including 
structured notes), create synthetic liabilities at lower cost then 
actual debt with the same characteristics. Other derivative contracts 
are used as macro hedges against portfolio level risks. However, all 
swaps expose an Enterprise to counterparty credit risk, which is the 
risk that the counterparty may default on its contractual obligation at 
a time when the derivative contract has a positive market value to the 
Enterprise.

[[Page 18159]]

    Currently, the Enterprises limit their exposure to counterparties 
by entering into swap transactions only with counterparties rated 
investment grade and by requiring all counterparties to execute 
collateral pledge agreements. These pledge agreements require any 
counterparty currently rated or subsequently downgraded to a less than 
a AAA credit rating to post collateral to the extent that net losses on 
its contracts \170\ with an Enterprise exceed threshold levels. The 
threshold levels vary based on the counterparty's rating. The 
Enterprises do not require AAA-rated counterparties to post collateral, 
but if any counterparty is downgraded, the collateral pledge agreements 
subjects it to the more stringent collateral requirements of its new 
lower rating. Freddie Mac, in its comments, describes additional 
measures it uses to mitigate counterparty risk, which include using 
contracts with close-out and netting arrangements that allow Freddie 
Mac to offset losses on one contract with a particular party against 
gains on another contract. Freddie Mac also described its practice of 
requiring guarantees from well-capitalized parent companies and of 
periodically marking each contract to market at full replacement value.
---------------------------------------------------------------------------

    \170\ These losses are calculated on a mark-to-market basis, 
because most derivatives involve features, such as payment streams 
and options, the values of which fluctuate with changes in the yield 
curve.
---------------------------------------------------------------------------

    In commenting on the ANPR, Freddie Mac stated that its management 
of credit risk on derivatives is such that the stress test should 
specify no losses due to counterparty default. Freddie Mac suggested 
that any losses would be covered adequately by the 30 percent add-on 
that the 1992 Act requires for management and operations risk and by 
the minimum capital standard. ACB, commenting generally on the subject 
of counterparty risk, stated that where collateral is provided, the 
risk of counterparty failure is remote. ACB suggested that, at most, a 
straightforward ``haircut'' on ``in the money'' derivative positions 
should be applied.
    After consideration of these comments, OFHEO determined that 
reducing the haircuts for derivative counterparty risk by 80 percent 
from haircuts on other types of third party credit risk would provide 
appropriate recognition for Enterprise collateral agreements. However, 
OFHEO did not agree with Freddie Mac that the stress test should apply 
no haircuts. There always remains the possibility that counterparties 
could default on their obligations due to a sudden calamity that could 
prevent collateral from being posted. Also, collateral values can 
decline over time or collateral may be subject to competing claims. 
Sudden business bankruptcies and decline or impairment of collateral 
value would be even more likely than usual under the harsh economic 
circumstances of the stress test. Accordingly, and for the same reasons 
that similar haircuts are applied to mortgage credit enhancements and 
non-mortgage investments, OFHEO proposes to specify losses in the 
stress test due to failure of derivative counterparties.
    OFHEO proposes to take into account the amount of loss due to 
derivative counterparty default as follows. As illustrated in Table 29, 
the stress test applies haircuts that increase linearly (by equal 
amounts) each month to the net payments from derivatives with a given 
counterparty over the term of the contracts with that counterparty. 
That is, if the Enterprise's net swap position across all contracts 
with a particular counterparty imply cash payment to the Enterprise 
during a given month, that cash payment is reduced (``haircut'') by an 
amount determined by the public credit rating of the counterparty and 
period in which the payment is owed. The calculation is performed for 
each counterparty and for each month in which a counterparty has swap 
agreements with the Enterprise. The cash flows for all derivatives with 
each counterparty are netted, except swaps that exchange into U.S. 
dollars any currency in which Enterprise debt may be denominated. 
Haircuts are applied separately to these derivatives, as explained 
below.
[GRAPHIC] [TIFF OMITTED] TP13AP99.213


[[Page 18160]]


    The haircuts reflect the probability that some counterparties will 
be unable to meet their obligations during the stress period. Haircuts 
become progressively larger as the counterparty rating decreases, with 
parties rated BBB or lower and unrated parties receiving the most 
severe haircut. The haircut for each rating category is cumulative 
rather than additive. It increases linearly for each month of the 
stress period, beginning in the first month of the stress test until 
the full amount of the discount is reached in the 120th month. Table 29 
reflects the size of the haircut at the end of each 12 month period 
during the stress test. Rating downgrades are not modeled. Instead, 
deterioration in the financial condition of counterparties due to the 
stressful environment is reflected in the linear increase of the 
haircuts.
    The proposed approach recognizes that both Enterprises utilize 
netting and close out arrangements such as those described by Freddie 
Mac in its comments. If OFHEO determines that not all derivatives with 
a particular counterparty are covered by a single arrangement, the 
derivatives' cash flows will not all be netted together. Instead, the 
stress test will group the derivatives by netting agreement and apply 
haircuts separately to the net cash flow for the derivatives covered by 
each agreement. For derivatives covered by no netting agreement, the 
haircut would be applied on an instrument by instrument basis to any 
derivatives that are ``in the money.'' In the event that any 
derivatives contracts do not include standard Enterprise collateral 
agreements, the haircut percentages imposed will be those in Table 27 
in section III.C., Mortgage Credit Enhancements.
    As mentioned above, the stress test will apply haircuts separately 
to swap agreements that exchange into U.S. dollars any other currency 
in which Enterprise debt may be denominated. Because these agreements 
entail the Enterprise receiving payment denominated in other 
currencies, which the stress test does not model, the stress test 
cannot net them against more usual interest rate swaps. Neither can the 
stress test net these agreements against each other, since they use 
variety of currencies. Therefore, the stress test applies haircuts to 
each individual contract. Because the collateral agreements and 
investment ratings do not differ for the counterparties to these 
agreements, the stress test applies the same counterparty haircut 
percentages to them as it does for interest rate swaps. However, the 
haircut is applied to the `pay' side of these contracts rather than to 
the `receive' side. The effect will be a loss on each swap transaction 
equal to the haircut amount. This approach recognizes that the 
Enterprises use these swap agreements only to match a debt position for 
which the swap agreement is a hedge.

E. Non-Mortgage Investments

    In addition to mortgage investments, the Enterprises hold non-
mortgage investments \171\ that include Treasury securities, federal 
funds, time deposits, Eurodollar deposits, asset-backed securities 
\172\ (ABS), corporate securities, and state and municipal bonds.\173\ 
As of December 31, 1997, non-mortgage investments at Fannie Mae 
constituted about $66.8 billion (17 percent of on-balance sheet assets) 
and $13.8 billion (7.0 percent) at Freddie Mac.
---------------------------------------------------------------------------

    \171\ Both OFHEO and HUD are authorized to regulate the 
Enterprises' non-mortgage investment activities. OFHEO has specific 
authority to ensure that the Enterprises are adequately capitalized 
and operating safely (1992 Act, section 1313 (12 U.S.C. 4513)), and 
HUD has general regulatory authority over the Enterprises to ensure 
that the purposes of the 1992 Act are accomplished (1992 Act, 
section 1321 (12 U.S.C. 4541)). While HUD's current regulations do 
not contain specific provisions about the Enterprises' non-mortgage 
investments, HUD issued an advance notice of proposed rulemaking 
(ANPR) seeking comment about the need for it to regulate such 
investments. (62 FR 68060, December 30, 1997)
    \172\ ABS are similar to MBS but are backed by nonmortgage 
assets, such as receivables on car loans and credit cards.
    \173\ Although they are generally tax-exempt, for purposes of 
the stress test, mortgage revenue bonds (MRBs) are not included in 
the category State and municipal bonds. MRBs are discussed in the 
section titled ``other housing assets.''
---------------------------------------------------------------------------

    OFHEO considered several issues related to how the stress test 
should model the cash flows associated with the Enterprises' non-
mortgage investments. The first issue concerns whether the stress test 
should model cash flows from such investments at the instrument level 
or at an aggregated level. Such aggregation entails grouping individual 
instruments with similar terms and risk characteristics and modeling 
the group as a single instrument. The proposed stress test models the 
cash flows of all non-mortgage investments on an instrument-by-
instrument basis. Evaluating whether to model non-mortgage investments 
on an instrument versus an aggregated level represents a trade-off 
between accuracy, model complexity, and information system resources. 
Instrument level modeling provides greater accuracy than modeling 
aggregated investments because aggregating instruments may result in 
losing information. On the other hand, instrument level modeling may 
result in added complexity and require additional information system 
resources. Neither of these concerns poses a significant constraint in 
the case of modeling the Enterprises non-mortgage investments. 
Accordingly, OFHEO believes that modeling cash flows from non-mortgage 
investments is practicable and appropriate. With respect to complexity, 
the model for generating cash flows uses the same types of information 
for an individual instrument as it would for a synthetic instrument 
representing a group of actual instruments. With respect to information 
resources, OFHEO systems are capable of processing the large number of 
individual investments in a reasonable amount of time.
    The second issue concerns whether there should be any simplifying 
assumptions in modeling the cash flows associated with non-mortgage 
investments. OFHEO has decided to include the following three 
simplifying assumptions which will facilitate this modeling, without 
having a significant effect on the risk-based capital requirement. 
First, for investments with common characteristics, the stress test 
specifies one payment frequency for those instruments. Second, the 
stress test standardizes prepayment speeds for ABS, i.e., how fast 
principal (both scheduled principal and prepayments) is returned. 
Third, the stress test will not apply different ABS prepayment speeds 
in different interest rate environments, because ABS typically pay off 
quickly and therefore are not significantly affected by interest rates. 
In addition, the effect of specifying different prepayment speeds on 
the risk-based capital requirement would not be significant, and would 
add unreasonable additional complexity to the stress test.
    OFHEO next considered whether the proposed stress test should, with 
respect to non-mortgage investments, model their credit risk, i.e., the 
risk that there will be a default on an instrument. OFHEO has 
determined that it is appropriate to model such credit risk because 
some issuers would be unable to meet their obligations during the 
stress period. The proposed stress test ties the credit quality of non-
mortgage investments to the credit rating specified by one or more 
nationally recognized public rating organizations, such as S&P or 
Moody's. While public offerings usually have a single rating, they 
occasionally have split ratings. In the case of split ratings, the 
stress test will use the lowest rating.
    The stress test first generates cash flows for a given instrument 
and then reduces those cash flows by a specified percentage (i.e., 
``haircut'') based on the public rating organization. The percentage 
haircut increases as the

[[Page 18161]]

rating decreases so that a highly-rated instrument will have a lower 
haircut than a lower rated instrument. In the absence of a rating, the 
stress test would apply the lowest rating category. The haircuts 
increase linearly (i.e., in equal increments) during each month of the 
stress period. Table 29 illustrates the ending haircuts in the 120th 
month for each rating category. Refer to section III. C., Mortgage 
Credit Enhancements for the discussion of the proposed haircuts.
[GRAPHIC] [TIFF OMITTED] TP13AP99.214

    An instrument that is unrated or has a rating that is below 
investment grade will receive the most severe haircut. This reflects 
OFHEO's determination that it is appropriate for the stress test to 
reflect high credit losses for non-mortgage investments that are more 
risky than the instruments that are now included in the Enterprises' 
current holdings. The Enterprises' non-mortgage investments are 
currently of high quality,\174\ but the Enterprises are not statutorily 
or otherwise legally required to invest solely in high quality 
instruments. It is possible that an Enterprise might change its 
investment practices to include non-mortgage investments with lower 
credit quality.
---------------------------------------------------------------------------

    \174\ For instance, in response to HUD's ANPR, Fannie Mae 
commented that ``Nearly two-thirds of the [liquid investment] 
portfolio is rated AAA (or the equivalent), and nearly all (98 
percent) of the portfolio is rated at least A (or the equivalent).
---------------------------------------------------------------------------

F. Other Housing Assets

    Other housing assets are a small category of Enterprise assets that 
need to be modeled differently than retained whole loans and mortgage-
backed securities are modeled. They are primarily mortgage revenue 
bonds (MRBs). They also include certain Real Estate Mortgage Investment 
Conduits (REMIC) securities issued by private entities and some 
interests in partnerships and joint ventures. These assets have cash 
flow characteristics that vary from investment to investment, and the 
data required to model cash flows precisely is not readily available. 
The impact of how these assets are modeled on the stress test results 
will be modest.
1. Mortgage Revenue Bonds
    Mortgage revenue bonds are issued by state and local housing 
authorities to raise funds for single family and multifamily mortgage 
lending programs. Both single and multifamily mortgage revenue bonds 
are secured by mortgage loans, reserve funds, and other credit 
enhancements. Government subsidies to some multifamily projects also 
provide implicit credit support. Most MRBs are tax exempt. The 
Enterprises are permitted to hold up to two percent of their assets in 
tax exempt securities.
    OFHEO considered whether to model MRB cash flows on individually or 
on an aggregated basis. The stress test models MRB cash flows bond-by-
bond. Although one modeling approach is to group securities and use 
weighted average interest rates and terms to calculate future cash 
flows, OFHEO determined that calculating cash flows individually is 
simpler. Available computer hardware and software allow the calculation 
of cash flows on many individual securities in almost the same amount 
of time it takes to calculate a single cash flow using average rates 
and maturities for a group. In addition, any decrease in precision that 
might be introduced through pooling is avoided.
    OFHEO next considered whether to calculate interest and principal 
payments for the MRBs based on each security's actual structure or to 
use a proxy for calculating bond payments. Interest on MRBs is paid at 
the bond rate on the principal amount of the bond, but MRBs have 
different schedules for principal repayment. In some MRBs, the issuer 
may use principal repayments from mortgages associated with one MRB 
transaction to retire bonds from another transaction. In many 
transactions, issuers have substantial discretion to retire bonds 
early. There is no single source of information on MRB structures, nor 
is the information readily available from multiple sources.
    OFHEO determined that the modeling approach used to calculate cash 
flows on Ginnie Mae securities would provide a reasonable proxy for 
cash flows on mortgage revenue bonds. Specifically, the bonds are 
modeled as passthrough securities, with the underlying mortgage 
collateral bearing a coupon 75 basis points higher than the bond 
coupon. Although MRB payments are not passthroughs of mortgage loan 
payments, the MRB payments are related to the mortgage payments. MRB 
payments and Ginnie Mae security payments would be affected similarly 
by loan terminations and by economic conditions. Further, borrowers 
benefiting from MRB programs are similar to borrowers for the FHA and 
VA loans that collateralize Ginnie Mae securities, and the loan 
characteristics are similar. Therefore, the stress test calculates cash 
flows for MRBs essentially the same way that it calculates cash flows 
for Ginnie Mae securities. It amortizes the bond principal using loan 
termination rates for FHA and VA loans that have the maturity of the 
MRB and coupons equal to the MRB coupon plus a spread.
    OFHEO considered whether to design a modeling approach specifically 
for multifamily MRBs or to model cash flows for single family and 
multifamily MRBs the same way. The stress test models cash flows for 
multifamily MRBs as though they were single family Ginnie Mae 
securities, just as it does for single family MRBs.
    Modeling multifamily MRB cash flows according to the structures of 
the securities is hampered by the same data problems that affect 
modeling single family MRB cash flows. Therefore, the stress test needs 
to use a proxy. The choice of proxy is limited. Information on 
Government-insured multifamily loans is not readily available. 
Enterprise multifamily MBSs are not an acceptable proxy for multifamily 
MRBs, because the Enterprises' multifamily loans differ from the loans 
that collateralize multifamily MRBs, and multifamily MBSs pay 
differently from multifamily MRBs. Because multifamily MRBs are a very 
small percentage of each Enterprise's assets and their impact on risk-
based capital is minimal, OFHEO determined that single family Ginnie 
Mae securities would be used as a proxy for multifamily MRBs.
    The stress test addresses the credit risk associated with MRBs by 
applying the haircuts that are tied to the public

[[Page 18162]]

credit ratings of the bonds. The haircuts will be in the same amount 
and will be applied in the same way as haircuts for credit enhancements 
and non-mortgage investments. Currently, a sizeable majority of the 
MRBs held by the Enterprises are rated AA and above.
2. Private Label REMICs
    The Enterprises own a small amount of REMIC securities that are 
issued by private sector entities. For most of these securities, the 
information that would be necessary to calculate cash flows for the 
REMIC collateral and thus for the REMIC securities is not readily 
available.
    As with mortgage revenue bonds, OFHEO considered whether to model 
the cash flows of the REMIC securities or to model cash flows using a 
proxy. The stress test uses a proxy. The stress test models cash flows 
for private REMIC securities using the same modeling approach as it 
uses for MRBs. The stress test amortizes the principal of the REMIC 
securities using the appropriate termination rates for the coupons and 
maturities.
    Data that is needed to project precise cash flows is not readily 
available. The costs of developing the data and reverse engineering the 
REMIC securities are not warranted by any incremental refinement that 
might result. Most of the REMIC securities held by the Enterprises are 
rated AAA. The credit risk of the private issue REMICs will be taken 
into account by applying the same haircuts as those used for MRBs.
3. Interests in Partnerships and Joint Ventures
    OFHEO decided not to model gains or losses on interests in 
partnerships or joint ventures, a category that totals less than $200 
million, or less than 0.03 percent of Enterprise assets. These assets 
carry little credit risk but generate tax losses that benefit the 
Enterprises. OFHEO has determined that projecting cash flows and tax 
benefits of these assets would create significant additional complexity 
in the stress test, without having any material impact upon the risk-
based capital requirements. Accordingly, the stress test treats these 
assets as though they remain on the balance sheet with no run-off and 
no associated income. In the future, if these investments become a 
larger proportion of either Enterprise's book of business, OFHEO will 
reconsider how they are modeled in the stress test.

G. Commitments

    The 1992 Act specifies that during the stress period the 
Enterprises will purchase no additional mortgages nor issue any MBS, 
except that--

[a]ny contractual commitments of the enterprise to purchase 
mortgages or issue securities will be fulfilled. The characteristics 
of resulting mortgage purchases, securities issued, and other 
financing will be consistent with the contractual terms of such 
commitments, recent experience, and the economic characteristics of 
the stress period.\175\
---------------------------------------------------------------------------

    \175\ 1992 Act, section 1361(a)(3)(A) (12 U.S.C. 4611(a)(3)(A)). 
The 1992 Act does provide for later amendment of the rule to address 
new business during the stress period, but not until after this 
regulation is final. The 1992 Act requires that, within one year 
after this regulation is issued, the Director of the Congressional 
Budget Office and the Comptroller General of the United States shall 
each submit to the Congress a study of the advisability and 
appropriate form of any new business assumptions to be incorporated 
in the stress test. Section 1361(a)(3)(C) (12 U.S.C. 4611(a)(3)(C)). 
Subparagraph 1361(a)(3)(B) (12 U.S.C. 4611(a)(3)(B) authorizes the 
Director to consider these studies and make certain new business 
assumptions. However, that subparagraph does not become effective 
until four years after this regulation is issued.

    The term ``contractual commitments'' generally refers to binding 
agreements that the Enterprises enter into with seller/servicers to 
purchase mortgages or to swap mortgages for MBS. The term also refers 
to agreements to sell such securities to investors. The total of 
outstanding purchase or swap commitments at both Enterprises at any 
point in time is generally in the tens of billions of dollars. The 
following discussion describes the issues faced by OFHEO in determining 
the appropriate volume and characteristics of mortgages delivered under 
commitments.
1. Definition of the Term ``Commitment''
    The proposed risk-based capital regulation incorporates, by 
reference, the definition of ``commitment'' from OFHEO's minimum 
capital regulation. OFHEO defines ``commitment'' in the minimum capital 
regulation as follows:

    Commitment means any contractual, legally binding agreement that 
obligates an Enterprise to purchase or to securitize mortgages.\176\
---------------------------------------------------------------------------

    \176\ 12 CFR 1750.2; See 61 FR 35610, July 8, 1996 (explanation 
of definition).

    This definition includes ``mandatory'' and ``optional'' 
commitments. Mandatory commitments bind the seller to deliver, and the 
Enterprise to accept, a certain volume of mortgages. Optional 
commitments are delivery contracts that commit the Enterprises to 
purchase or swap a specified volume of loans, but do not commit the 
seller to deliver any loans. The definition includes commitments that 
do not specify fixed prices or volume, but otherwise legally bind an 
Enterprise.
    Freddie Mac, the only ANPR commenter to address the definition of 
commitments, recommended that contractual commitments be defined to 
include only agreements that legally bind the Enterprises to purchase 
mortgages. According to Freddie Mac, ``[u]nder fundamental contract 
law, an agreement is only binding if all of its key terms are included 
and agreed upon.'' Freddie Mac further stated that price and volume are 
two key terms and that only commitments containing this information are 
legally binding contracts for the Enterprises. This comment suggests 
that OFHEO should not model commitment contracts that do not contain 
price and volume information (e.g., master commitments for cash 
purchases).
    OFHEO has found no reason to adopt a different definition for 
purposes of computing risk-based capital from that used for computing 
minimum capital. In both cases, the term should mean any legally 
binding agreement that obligates an Enterprise to purchase or 
securitize mortgages. OFHEO does not believe it necessary or 
appropriate to restrict the definition of the term ``commitment'' by 
reference to price, volume, and fees, because agreements may be legally 
binding even when they lack specificity on all terms.\177\ It would add 
unnecessary complexity to attempt to reflect the myriad details of 
diverse State contract laws in the regulatory definition. Moreover, to 
do so would be inadvisable in light of Congress' specific concerns 
regarding the need for capital to support commitments and other off-
balance-sheet obligations. For example, in discussing the need for the 
capital requirements of the 1992 Act, Congress expressed the concern 
that the risk in off-balance-sheet obligations had not been captured 
under prior capital standards:
---------------------------------------------------------------------------

    \177\ See Restatement (Second) of Contracts Sec. 204 (1981).

    The capital provisions of the GSEs' charter Acts limit their 
debt to 15 times their capital unless HUD sets a higher ratio * * * 
This is unsatisfactory because no capital need be held against the 
GSEs' $750 billion of off balance sheet guarantees * * *\178\
---------------------------------------------------------------------------

    \178\ S. Rep. No. 102-282, at 11 (1992) (referring to the 
existing capital standard, which the 1992 Act repealed).

Recognizing this concern, it would be inappropriate for OFHEO to 
promulgate a narrow definition that could exempt certain legally 
binding commitments from the risk-based capital requirement.
    Freddie Mac also recommended a definition of commitments that 
excludes all optional commitments, including those containing price and 
volume

[[Page 18163]]

information. Specifically, Freddie Mac suggested the following 
definition:

    Contractual commitment means an obligation of an Enterprise that 
legally binds the Enterprise to issue securities or purchase 
mortgages and legally binds a third party to purchase securities or 
deliver mortgages, and that sets forth all terms of the transactions 
including price, volume, and fees.

(emphasis added).
    The phrase ``legally binds a third party'' would define a 
commitment to include only an agreement that binds the counterparty to 
deliver mortgages or to purchase securities, thus excluding optional 
commitment contracts.
    OFHEO disagrees with this comment and includes optional commitments 
in the stress test definition. The 1992 Act is clear on this issue, 
because it refers to ``commitments of the enterprise to purchase * * * 
or issue'' (emphasis added) but includes no requirement that the 
commitment bind others to deliver mortgages. Optional commitments 
obligate the Enterprise to purchase and are optional only for the 
seller. Therefore, optional commitments fall squarely within the 
statutory definition.
2. Retained vs. Securitized Mortgages
    The proposed regulation specifies that all loans delivered under 
commitments are packaged into securities (securitized) and sold. This 
specification avoids requiring OFHEO to predict business decisions by 
the Enterprises that are highly judgmental and impossible to predict 
accurately. OFHEO recognizes that in practice the Enterprises make day-
to-day decisions to sell or retain loans. However, the simple rule 
proposed by OFHEO avoids the complexity of attempting to model such 
business decisions.
    ACB commented that ``[a]ny loans not presold by the GSEs should be 
assumed to be retained in portfolio and carry both the credit and IRR 
[interest rate risk] exposure.'' OFHEO disagrees with ACB's suggestion, 
because it would add undue complexity to the stress test. At no time 
are the Enterprises obligated by the terms of a commitment to retain 
mortgages in portfolio. Furthermore, retaining these mortgages in 
portfolio in the stress test would require OFHEO to predict how the 
Enterprises would finance and hedge the interest rate risk associated 
with the purchases. These predictions would increase greatly the 
complexity of the stress test and introduce assumptions about future 
Enterprise management, which OFHEO, as a general rule, has found 
inappropriate in a ``no new business'' stress test.
    For these reasons, OFHEO determined that proposing that all loans 
delivered under commitments will be securitized and sold is a 
reasonable, straightforward approach.
3. Modeling Delivery Percentages
    The stress test will provide that, in the down-rate scenario, 100 
percent of all loans that the Enterprises are obligated to accept will 
be delivered and, in the up-rate scenario, 75 percent of those loans 
will be delivered. As explained below, OFHEO considered the relevant 
comments on this issue and found the proposed rule to be a reasonable 
and practical method of estimating the volume of new mortgages that 
will be delivered in the stress test.
    In determining the appropriate percentage, OFHEO looked first to 
the 1992 Act, which provides that commitments will be ``fulfilled.'' In 
contractual parlance this term means that the parties will fulfill 
their contractual obligations under these instruments. Therefore, OFHEO 
decided to propose a simple rule, based upon estimates of the delivery 
volumes that would be likely to occur if both parties fulfill those 
obligations.
    Not all mortgages that the Enterprises are obligated to accept 
under commitments are actually delivered. Optional commitments obligate 
the Enterprise to purchase up to a specified dollar amount of 
mortgages, but do not obligate sellers to deliver any mortgages. They 
can be fulfilled by both parties even though fewer than all the loans 
specified in the commitment are delivered. Under a mandatory 
commitment, the Enterprise is also obligated to purchase a specified 
dollar value of loans, but the seller fulfills the contract either by 
delivering the specified volume of loans or by paying a ``pair-off'' 
fee specified in the commitment agreement. These fees are a form of 
liquidated damages that, under the terms of mandatory commitments, are 
payable by sellers who fail to deliver the full amount of mortgages 
specified in the commitments. Therefore, under either type of 
commitment, less than all the stated mortgage volume may be delivered.
    As mentioned above, the proposed regulation specifies that, in the 
down-rate scenario of the stress test, 100 percent of loans the 
Enterprises are obligated to buy or securitize will be delivered under 
all types of commitments. In the up-rate scenario, 75 percent of those 
loans will be delivered. This specification reflects the fact that when 
interest rates decline significantly, the volume of new purchase 
mortgages and mortgage refinancings generally increases. Therefore, in 
the down-rate scenario, lenders should have plenty of mortgage volume 
to meet or fill all commitments. In contrast, when interest rates rise 
significantly, the demand for mortgages tends to fall. Therefore, in 
the up-rate scenario, sellers would find it difficult to generate 
enough mortgages to meet outstanding commitments. Because the proposed 
regulation provides that all loan deliveries will be made in the first 
three to six months of the stress period (see section III.G.4., 
Delivery Timing below), those deliveries are particularly sensitive to 
short-term changes in interest rates. Thus, the steeply rising rates in 
the first few months of the up-rate scenario have a significant impact 
upon delivery percentages. It would be inappropriate, however, to 
assume that loan deliveries would decline more than 25 percent, given 
that many of the commitments are mandatory and that existing home 
purchase contracts will require financing. Lenders will also have a 
certain volume of outstanding loan commitments with locked rates, most 
of which would close.
    Figure 3 below shows that, during the most recent increase in rates 
of any significance (the first half of 1994), a three month increase in 
interest rates of 150 basis points led to a drop in market origination 
volume of roughly 30 percent. Also, during the 12-year period shown, 
market volumes never decreased over any three-month period by more than 
25 to 30 percent. Because the stress test will include rate changes of 
150 basis points or less in the first quarter, the data led OFHEO to 
conclude that a 75 percent delivery rate would be a reasonable 
specification for the up-rate scenario of the stress test.
    The proposed regulation does not credit the Enterprises with income 
from ``pair-off fees'' in the up-rate environment for two reasons. 
First, there is no usable data on the payment of these fees or on the 
percentage of deliveries under commitments. Therefore, attempting to 
model these fees would require estimating, with no supporting data, the 
percentages of loans to be delivered under mandatory, as opposed to 
optional, commitments. Second, the fees are not always charged by the 
Enterprises. Therefore, including the fees would require OFHEO to 
speculate how frequently or under what circumstances the Enterprises 
would impose them.

[[Page 18164]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.371


    In its ANPR comments regarding delivery percentages, Freddie Mac 
recommended that OFHEO develop an econometric model of delivery 
percentages for commitments. This model would be based on recent 
prepayment experience of each Enterprise and the prepayment rates 
produced by OFHEO's default/prepayment model. The model that Freddie 
Mac recommended would compute commitment delivery percentages as 
follows:
    1. OFHEO would determine a means of estimating the extent to which 
sellers would fulfill mortgage purchase commitments by (a) delivering 
mortgages or (b) paying a pair-off fee without delivering the 
mortgages.
    2. Then, OFHEO would determine a stress period delivery percentage 
under all commitments to reflect the effect of stress period 
conditions. Specifically, Freddie Mac suggested that a good 
approximation of this effect would be the ratio of the sum of the 
prepayment rate and the purchase-growth rate (rate of increase or 
decrease in the volume of loans purchased by the Enterprises) during 
the relevant portion of the stress period to the sum of the prepayment 
rate and the purchase growth rate during a recent period immediately 
prior to the stress period. This ratio would be multiplied by a 
``baseline'' delivery percentage, which is the normal delivery 
percentage during times of little interest rate fluctuation. Under this 
approach, the stress test delivery percentage would be expressed as 
follows:
[GRAPHIC] [TIFF OMITTED] TP13AP99.379

The stress period growth rate would be zero until such time as OFHEO 
included new business assumptions in the stress test, and the stress 
period delivery percentage would not be allowed to exceed 100 percent.
    Freddie Mac bases its approach on two assumptions. First, the 
volume of outstanding commitments at the beginning of the stress period 
(i.e., the then current volume of outstanding commitments) is assumed 
to be related to the volume of mortgage purchases that the Enterprises 
and sellers anticipated at the time they entered into the commitments. 
Second, the sellers' actual rate of deliveries during the stress period 
under outstanding commitments is assumed to be closely related to 
actual mortgage purchase activity during the relevant portion of the 
stress period.
    OFHEO agrees with these assumptions and used them to determine 
appropriate stress test delivery percentages. OFHEO also agrees that an 
econometric approach such as that proposed by Freddie Mac might provide 
a relatively sophisticated representation of what would actually occur 
under stress test conditions. However, there are insufficient data to 
construct such a model of commitments at this time. Historical data 
available to OFHEO do not reveal what percentages of commitments have 
been delivered. The Enterprises have provided descriptions of 
commitment types and made statements about their general business 
practices and the length of and delivery patterns of commitments. 
However, OFHEO has found available data are inadequate to associate 
actual mortgage purchases with commitments. Therefore, neither of the 
two steps in the Freddie Mac proposal currently is possible. There is 
no source of data to determine a reasonable estimate of pair-off fee 
payments or to determine a historical baseline delivery percentage.
    ACB's ANPR comments suggested that a historically based dropout 
factor be applied to account for failure to ``make/take delivery by 
counterparties.'' The lack of historical data regarding actual delivery 
percentages under commitments limits the accuracy with which such a 
factor or factors can be calculated. However, OFHEO proposes an 
approach consistent with the ACB comment. The stress test specifies 
fixed delivery percentages for commitments in the down-rate and the up-
rate scenarios. These percentages are based on historical information, 
displayed in Figure 3, about mortgage volume in the entire mortgage 
market during periods when rates have risen and fallen sharply. This 
information demonstrates that declining interest rates are generally 
accompanied by or followed shortly by increases in the volume of

[[Page 18165]]

mortgage originations. Conversely, increasing interest rates tend to 
slow originations.
4. Delivery Timing
    Table 30 displays the timing of mortgage deliveries incorporated in 
the stress test for both interest rate scenarios. The specified 
delivery timing is consistent with the contractual terms of 
commitments, the experience of the mortgage market, and the interest 
rates that the 1992 Act specifies for the stress period.
[GRAPHIC] [TIFF OMITTED] TP13AP99.215

    This front-loaded delivery profile in both interest rate scenarios 
is consistent with the contractual terms of commitments, which usually 
specify that deliveries will occur within 60 days and in most other 
cases require delivery within 6 months. Also, at any point in time, 
most outstanding commitments (other than those made that day) will have 
only a part of the specified delivery period remaining. For these 
reasons, OFHEO believes it is appropriate to project that deliveries 
under commitments would drop to zero over the first three to six months 
of the stress period, with half or more of those deliveries likely to 
occur in the first two months.
    For the same reasons that delivery percentages are higher in the 
down-rate than in the up-rate environment, OFHEO believes it is 
appropriate to provide for faster deliveries when interest rates are 
falling than when they are rising. Mortgage origination experience 
demonstrates that decreasing interest rates tend to cause significant 
increases in mortgage originations. Therefore, it is reasonable to 
specify that deliveries occur sooner when interest rates in the stress 
test rapidly decline than when they rise.
    ACB commented about delivery timing, stating that OFHEO should 
assume scenarios that would be least advantageous to the Enterprises, 
whether they were buying loans or selling securities. Because there are 
no historical data on deliveries under commitments, the stress test 
specifies delivery timing consistent with observed historical patterns 
of mortgage originations. The delivery timing in the stress test is 
intended to be a reasonable approximation of what would occur under the 
stress test conditions specified in the 1992 Act, not necessarily what 
would be least advantageous to the Enterprises.
    Freddie Mac suggested two delivery timing options in its comments 
on the ANPR. Freddie Mac recommended that OFHEO assume that purchases 
occur uniformly over the weighted average maturity of outstanding 
commitments. Alternatively, Freddie Mac suggested a formula that was 
derived by assuming that commitments expire uniformly and that 
purchases are uniform during the term of each commitment. Freddie Mac 
described the latter approach as unnecessarily complex and unlikely to 
affect the overall capital requirement associated with commitments, but 
indicated it was nevertheless an acceptable means to estimate delivery 
timing. OFHEO was concerned about a lack of empirical support for 
either of Freddie Mac's alternative recommendations, however, and has, 
therefore, chosen to propose the relatively simple delivery timing 
described above.
5. Loan Mix Distribution
    The type, term, LTV ratio, coupon, and geographic mix of loans 
(``loan mix'') that are delivered under commitments can have a 
significant impact upon associated credit losses in the stress test.
    The proposed regulation provides that, with the exception of coupon 
interest rates, the loan mix delivered under commitments at each 
Enterprise is the same as the mix of loans securitized by each 
Enterprise that were originated during the immediately preceding six-
month period. This approach reflects the view that a reasonable 
indicator of the mix of loans that might be delivered in the near 
future is the mix of loans delivered in the recent past. To the extent 
that an Enterprise has been buying a larger or smaller percentage of 
loans with a particular characteristic over the past six months, the 
stress test effectively continues that mix. OFHEO's proposed approach 
does not differentiate the loan mix of deliveries in the up-rate and 
down-rate scenarios.
    To reflect movements in stress test mortgage interest rates, the 
stress test uses two different ``conventional mortgage rate'' series, a 
30-year rate and a 15-year rate, described earlier in section III. B., 
Interest Rates, to determine mortgage rates on newly delivered fixed-
rate mortgages.\179\ It uses

[[Page 18166]]

the one-year CMT, along with the average margin for ARM loans
---------------------------------------------------------------------------

    \179\ The stress test assumes that mortgage interest rates on 
seven-year balloon mortgages are 50 basis points less than 30-year 
conventional mortgage rates in the down-rate environment, and equal 
to the 30-year rate in the up-rate environment.
---------------------------------------------------------------------------

originated within the past six months, to determine mortgage rates on 
newly delivered ARMs.
    In its ANPR comments, Freddie Mac recommended two methods of 
modeling loan mix. Freddie Mac recommended that the loan mix of 
mortgages delivered under commitments could be the same as the loan mix 
of the Enterprises' outstanding portfolios. Alternatively, Freddie Mac 
suggested that OFHEO look to historical experience and base the stress 
period mix on the mix during past up-rate and down-rate environments. 
Freddie Mac further commented that the mix of mortgages delivered under 
outstanding commitments should not be modeled based on recent mortgage 
deliveries. Its rationale was that the capital requirement associated 
with commitments could vary dramatically because of one-time special 
purpose transactions. Freddie Mac cited, as an example, the distorting 
effects created by an Enterprise purchase of a large Cost Of Funds 
Index (COFI) ARM portfolio representing 30 percent of a quarter's 
purchases.
    OFHEO did not adopt Freddie Mac's first suggestion because OFHEO 
believed that the mix of loans in an Enterprise's overall portfolio has 
only a limited relationship to the loans that will be delivered under 
current commitments. An Enterprise's portfolio at any given time 
contains loans obtained over many years during periods when economic 
conditions may have been quite different from the conditions that will 
exist at the start of the stress test. Current commitments, by 
contrast, are more likely to reflect Enterprise management's efforts to 
adjust the mix in its portfolio than they are to reflect the current 
mix in the portfolio. For these reasons, OFHEO found the current mix of 
loans at the Enterprises to be an unsatisfactory proxy for the mix of 
loans to be delivered under current commitments.
    Using a two-quarter (versus a one-quarter) period to compute the 
loan mix addresses Freddie Mac's concern over distortions created by 
occasional special purpose purchases. However, if large special purpose 
purchases of unusual mortgages occur frequently, it is appropriate that 
the stress test reflect some higher-than-usual risk by projecting 
continuing purchases of such mortgages.
    OFHEO also examined Freddie Mac's suggested alternative 
methodology--basing the loan mix on the ``mix that prevailed'' during 
prior up-rate and down-rate scenarios. Given the lack of historical 
data regarding deliveries under commitments, there is no direct 
evidence of what the experience of those deliveries has been. At best, 
information might be inferred from data regarding total deliveries, 
either at the Enterprises or in the market as a whole. However, OFHEO's 
research has found that, although long term increases in interest rates 
produce more ARMs and long term decreases produce more FRMs, short term 
changes in interest rates have little discernable affect on the ratio 
of ARMs to FRMs that are delivered to the Enterprises.
    For these reasons, OFHEO concluded that a more detailed and complex 
model based upon historical patterns of loan deliveries would be 
unlikely to improve the stress test's accuracy or sensitivity to risk 
or yield a significantly different result. OFHEO is confident that the 
proposed approach reflects a reasonable delivery mix for the stress 
test and that any fine-tuning that might result from a more complex 
model would have only an incremental effect. Also, because the proposed 
regulation specifies that these new loans will not be held in 
portfolio, they create little interest rate risk for the Enterprises. 
For all these reasons, OFHEO does not propose the type of detailed 
model of loan mix contemplated in Freddie Mac's comments.
    ACB also commented on loan mix, explaining that the mix of 
commitments should be ``as of the actual reporting date, subject to 
adjustment for any demonstrable `window dressing' practices by the 
GSEs.'' ACB assumed that data were available to determine what loan mix 
was specified under outstanding commitments at any point in time. As 
explained above, those data are not available. OFHEO interpreted 
``window dressing,'' to mean attempts that an Enterprise might make to 
alter temporarily the loan mix in its commitments just prior to the 
beginning of a particular quarter. OFHEO believes that the proposed 
approach, which looks to the mix of loans actually delivered over the 
last two quarters, addresses ACB's concern that an Enterprise might 
engage in ``window dressing.''
6. ``No New Business'' Rule
    World Savings commented in response to the ANPR that the stress 
test model should reflect ongoing business, not a wind down scenario. 
The comment stated that the assumption of no new business except for 
fulfillment of contractual commitments is ``fundamentally flawed,'' 
because it assumes the Enterprises will be prescient about the 
magnitude of the financial stress. World Savings commented that this 
assumption causes the test to underestimate the Enterprises' need for 
capital, because it causes their portfolios to shrink unrealistically. 
By contrast, a comment by Professor Yezer of George Washington 
University advocated placing limits on the size of the Enterprises' 
portfolios in the stress test. He concluded that ``one needs a model of 
[Enterprise] response to stress that makes sense in terms of modern 
financial theory of investment, not passive reaction to adverse changes 
as contemplated in the proposed rule.''
    Both of these comments suggest an alternative approach to new 
business that cannot be addressed at this time because the approach in 
the regulation is mandated by section 1361(a)(3) of the 1992 Act.\180\ 
That section requires that the initial risk-based capital regulation 
assume that the Enterprises take on no new business other than 
deliveries under existing commitments. After the issuance of the 
regulation, the 1992 Act requires studies by the Congressional Budget 
Office and the Comptroller General of the United States of the 
advisability and appropriate form of any new business assumptions to be 
incorporated in the regulation. Only after completion of those studies 
and their submission to the Congress may the Director, after 
considering them, propose amendments to the regulation that would 
incorporate new business assumptions during the stress period.\181\
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    \180\ 1992 Act, section 1361(a)(3) (12 U.S.C. 4611(a)(3)).
    \181\ 1992 Act, section 1361(a)(3)(B)-(D) (12 U.S.C. 
4611(a)(3)(B)-(D)).
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H. New Debt and Investment Rules

    During the stress period, an Enterprise invests and borrows, as 
needed, based on net cash flows. The stress test projects cash inflows 
and outflows for each month of the stress period. To the extent cash 
inflows exceed cash outflows in any month, the stress test must specify 
how an Enterprise employs the excess funds. Conversely, to the extent 
that cash outflows exceed cash inflows in any month, the stress test 
must specify how an Enterprise obtains the funds to cover the cash 
deficit.
    The 1992 Act provides no specific guidance for new debt issuance or 
new investments during the stress test. OFHEO sought new debt and new 
investment rules that would alter as little as possible the credit and 
interest rate exposures of an Enterprise generated by its initial 
asset, liability, and derivative positions.
    The proposed approach provides that all new debts and investments 
are short-

[[Page 18167]]

term instruments. More specifically, OFHEO proposes that the 
Enterprises fund all monthly net cash outflows during the stress test 
by issuing six-month discount notes. OFHEO also proposes that excess 
funds will be invested at the six-month Treasury bill rate in 
instruments that mature one month later.
1. Rationale for New Debt and New Investment Rules
    The purpose of a ``no new business'' stress test is to subject an 
Enterprise's business at the beginning of the stress period to adverse 
conditions, without introducing during the stress period any business 
responses to deteriorating business conditions that would tend to 
increase or decrease risk. Consistent with this purpose, the proposed 
new debt and investment rules are designed to project the effects 
during the stress period of specific stressful circumstances on the 
Enterprises, given the risks embodied in their business positions at 
the start of the stress test, while minimizing the introduction of any 
new risks.
    Accordingly, the stress test uses simple rules for the issuance of 
debt or the investment of liquidity. OFHEO intentionally does not 
propose to predict what asset-liability management decisions an 
Enterprise might make, predictions that would be difficult in any 
event.\182\
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    \182\ In a stress test that incorporates new business, the 
context would be different. Should OFHEO choose to incorporate new 
business in a later regulation, a different approach to asset-
liability management during the stress period could be appropriate. 
See 1992 Act, section 1361(a)(3)(C) (12 U.S.C. 4611(a)(3)(C)).
---------------------------------------------------------------------------

    The hazards of predicting the response of financial institutions to 
stressful conditions are well illustrated by the behavior of the 
thrifts during their financial crisis in the 1980s. While some 
institutions sought to limit or reduce their risks in that difficult 
environment, others made choices that greatly increased risk, in effect 
gambling that a fortunate turn of events would be their best chance of 
financial salvation. These choices largely determined the fate of the 
institutions. Similarly, incorporating activities that project the 
Enterprises's responses to the duration or severity of economic 
conditions during the early part of the stress period, while these 
conditions are deteriorating rapidly, could profoundly affect the 
Enterprises' financial performance in the stress period.
    For these reasons, the stress test makes no provision for an 
Enterprise to rebalance its portfolio as its asset and liability 
positions evolve during the stress test. The Enterprises are exposed to 
interest rate risk principally because changes in interest rates cause 
changes in the market (and economic) values of their long-term, fixed-
rate assets and liabilities, and of their derivative contracts. These 
changes in value are reflected in subsequent accounting statements of 
earnings and net worth.
    If an Enterprise's asset, liability, and derivatives positions are 
well matched, the effects will be minimal. But if, for example, an 
Enterprise were to fund long-term, fixed-rate mortgages with short-term 
debt, then an increase in market yields would cause the value of the 
mortgages to fall, but the value of the short-term debt would be little 
changed. In subsequent periods, interest income on the mortgages would 
be unaffected, but interest expenses would be higher because new debt 
would need to be issued at the new higher interest rate. Earnings and 
equity would suffer. Conversely, a fall in market yields would increase 
the value of the mortgages, and that higher value would be reflected in 
subsequent earnings and equity gains. If an Enterprise were to fund 
short-term assets with long-term, fixed-rate debt, its debt would 
change in value, but its assets would not, producing the opposite 
effect.
    If changes in interest rates continue over a period of time, then a 
decision to issue long-term debt or purchase long-term assets in the 
middle of the stress period would create a new source of changes in 
value over the remainder of the period. The effects of the change in 
interest rates on future earnings and equity would then reflect the 
changes in value of both the original positions and the new long-term 
debt or assets.
    In the proposed stress test, interest rates change substantially 
and continuously during the first year of the stress period and then 
are constant in the last nine years. If an Enterprise were projected to 
issue long-term debt or purchase long-term assets during the first 
year, the new investments would change in value during the remainder of 
the year and affect subsequent earnings and equity. Such an approach 
would distort the stress test's evaluation of starting risk positions.
    The proposed rule avoids these problems by making all new debt and 
investment short-term instruments. Investments are made in Treasury 
bills to avoid introducing credit risk; new debts are in the form of 
discount notes. Maturities of six-months were chosen as a 
representative short term.\183\
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    \183\ Recurring patterns in cash flows can cause an Enterprise 
to hold substantial volumes of new six-month investments at the same 
time that it has substantial volumes of new six-month debt 
outstanding. This creates an unnecessary balance sheet expansion. A 
more realistic solution would be to assume that maturities of new 
debts and investments were spread across a variety of terms less 
than one year. OFHEO proposes to approximate that result by assuming 
that any outstanding new six-month investments are redeemed at par 
at the end of each month.
---------------------------------------------------------------------------

2. Analysis of ANPR Comments
    In the ANPR, OFHEO posed several questions related to new debt and 
investments during the stress period. HUD and ACB recommended in their 
comments that OFHEO develop an econometric model of Enterprise funding 
decisions. OFHEO believes, however, that it would be inappropriate to 
build such a model. The factors that would have to be incorporated into 
such a model would require OFHEO to make complex judgments about the 
decisions an Enterprise's management might make in response to future 
economic conditions. HUD's comment that ``OFHEO may be able to base 
modeling of GSE liability management * * * on presumptions concerning 
how GSEs would formulate and exercise broad financial management 
objectives during a winddown'' would require similar judgments. ACB 
also commented that ``excess cash balances should be assumed to be 
deployed to minimize remaining interest rate risk exposure since the 
costs of such a hedging strategy are zero.'' OFHEO determined that this 
approach could change the risk profile of an Enterprise during the 
course of stress period and is, therefore, inappropriate for the stress 
test.
    Freddie Mac also addressed the question of new debt in the stress 
test. Freddie Mac proposed that OFHEO assume the Enterprises would 
generally adhere to their respective asset and liability management 
principles in a stress test environment. More specifically, the 
Enterprises would rebalance their portfolios of assets and liabilities 
during the stress period, in an attempt to maintain a specific 
relationship between the net effective maturity and net callability of 
assets and liabilities. Freddie Mac further suggested that OFHEO should 
use a simple rule that includes this concept for the issuance of new 
debt in the stress test. As a possible rule, Freddie Mac offered the 
following example: 30 percent short-term and 70 percent long-term debt 
in the up-rate scenario and 70 percent short-term and 30 percent long-
term debt in the down-rate scenario. The intent of the stress test is, 
however, to test the ability of an Enterprise's initial asset and 
liability mix to survive stressful conditions. Therefore, OFHEO 
preferred an approach that did not

[[Page 18168]]

actively alter the consequences of the interest rate risk exposure 
inherent in the Enterprises' business at the beginning of the stress 
period.
    At HUD's suggestion in its comments on the ANPR, OFHEO reviewed the 
role of new debt in the wind down scenarios described in HUD's 1987 
Report to Congress on FNMA, issued on September 27, 1989. Although 
OFHEO agrees with HUD that there is a close connection between 
investing cash, hedging activities, and liabilities, OFHEO believes 
that the purpose of the ``no new business'' stress test is to project 
the results of existing risk positions in stressful environments. This 
approach differs significantly from HUD's 1987 wind down scenarios, 
which were designed to project Fannie Mae's performance during an 
intentional wind down of Fannie Mae's mortgage portfolio in preparation 
for a hypothetical privatization of that Enterprise.

I. Operating Expenses

    Operating expenses include non-interest costs, such as those 
related to an Enterprise's salaries and benefits, professional 
services, property, and equipment. The operating expenses of each 
Enterprise comprise a relatively small portion of their overall 
expenses. For instance, in 1997, Freddie Mac's interest-related 
expenses were $10.6 billion, while its operating expenses were $495 
million. Similarly, Fannie Mae's interest-related expenses were $22.4 
billion, while its operating expenses were $636 million that year.
    The 1992 Act is silent on how operating expenses should be treated 
in the stress test. Nevertheless, the legislative history states that 
the Director should exercise discretion about variables such as the 
Enterprises' operating expenses, provided that they are ``reasonable 
and to the extent possible based on historical data.'' \184\ In 
addition, the stress test's treatment of operating expenses is guided 
by the 1992 Act's ``no new business'' requirement.\185\ That provision 
requires OFHEO to project the income and expenses associated with the 
existing business positions of the Enterprises over a ten-year period. 
The purpose of the ``no new business'' requirement is for the stress 
test to capture the risks of an Enterprise's existing assets, 
liabilities, and off-balance sheet obligations as of the beginning of 
the stress period. It is not intended to represent any combination of 
events that might occur in the actual course of an Enterprise's 
business activities.
---------------------------------------------------------------------------

    \184\ H.R. Rep. No. 102-206, at 65 (1991).
    \185\ 1992 Act, section 1361(a)(3)(A) (12 U.S.C. 4611(a)(3)(A)).
---------------------------------------------------------------------------

    In the proposed regulation, operating expenses decline during the 
stress period in direct proportion to the decline in the volume of each 
Enterprise's total mortgage portfolio (i.e., the sum of the outstanding 
principal balance of its retained and sold mortgage portfolios). The 
stress test first projects how an Enterprise's mortgage portfolio 
decreases during the stress period on a monthly basis. After 
determining the percent of these assets that remain at the end of any 
month during the ten-year stress period, OFHEO simulates the reduced 
operating expenses in each month by multiplying this percent by one-
third of the amount of the Enterprise's operating expenses in the 
quarter immediately preceding the start of the stress test. This 
computation is used to determine the Enterprises' operating expenses 
for each month of the stress period. As described in more detail in 
this section below, under this approach, the expense reduction pattern 
for the up-rate scenario will differ from the down-rate scenario, and 
the pattern within each scenario will vary depending on changes in the 
characteristics of an Enterprise's total mortgage portfolio.
    In the ANPR, OFHEO raised several questions about how the stress 
test should model operating expenses. These issues are considered 
below.
    OFHEO first considered whether there should be any reduction in 
operating expenses during the stress period. The stress test should 
include such a reduction because many of the Enterprises' operating 
expenses are tied to the size of their mortgage portfolios. Both 
commenters on this issue, Freddie Mac and ACB, supported this view.
    OFHEO next considered whether there should be a variable or 
straightline reduction in operating expenses. OFHEO determined that a 
variable reduction pattern would be more appropriate. The underlying 
characteristics of mortgages held or guaranteed by an Enterprise or the 
interest rate conditions of the stress period would substantially 
affect the rate of reduction in outstanding mortgage balances. Because 
a large portion of expenses are directly tied to outstanding loan 
balances, a variable reduction based on those balance patterns will 
better correspond with the cost reductions that would occur under the 
stress test scenarios.
    Notwithstanding this general approach, OFHEO notes that expenses in 
some categories are not closely tied to current loan balances. These 
expenses might be expected to change at different rates from loan 
balances in a stressful no-new-business environment. As Freddie Mac 
commented in response to the ANPR, a large portion of its operating 
expenses are associated with either new business or long-term research 
and development, including product and systems development, and so 
might be reduced more dramatically under a no-new-business assumption. 
Conversely, Freddie Mac stated that some other operating costs that are 
associated with ongoing costs of managing the mortgage portfolio are 
relatively fixed, i.e., they are independent of the size of the 
portfolio. On balance, tying expenses to loan balances will produce a 
reasonable approximation of an Enterprise's costs in the stress test 
scenarios.
    The proposed approach to modeling operating expenses differs from 
the recommendations made by ACB and Freddie Mac. Rather than a variable 
approach, these commenters favored a model applying a straightline 
reduction in operating expenses. Freddie Mac commented that a 
straightline approximation is sufficient, because the resulting capital 
requirement should depend primarily on the present value of the 
operating expenses and not on the exact timing of those expenses. 
However, OFHEO believes it is appropriate to adopt an approach that 
more precisely takes timing into consideration, because the timing of 
expenses affects an Enterprise's performance during the stress test and 
the resulting risk-based capital requirement. Furthermore, a 
straightline approach still requires a basis on which to determine the 
rate of expense reduction. The proposed approach simultaneously takes 
timing into account and determines the overall rate of reduction.
    The next issue concerned whether the model should reflect decisions 
that might be made by an Enterprise if it was intentionally winding 
down its business. On that issue, HUD recommended two alternative 
approaches: either that OFHEO model the behavior of an Enterprise on 
issues such as liability management, dividend policy, and operational 
management as if it were aware that a wind down is in effect, or that 
OFHEO proceed in a ``more formalistic fashion,'' i.e., without regard 
to whether they did or did not know. OFHEO analyzed this issue, not 
only within the context of operating expenses, but also as it relates 
to the underlying concepts of the stress test and many of its 
components. OFHEO determined that it would be inconsistent with the 
1992 Act and the overall purposes of the stress test for the

[[Page 18169]]

model to attempt to reflect decisions that would be made by an 
Enterprise that was intentionally winding down its operations. Instead, 
the stress test applies the alternative approach discussed by HUD in 
which an Enterprise would not know that a wind down was in effect. As 
discussed earlier, this approach is appropriate because the stress test 
is intended to capture the actual risks of an Enterprise's existing 
business as of the beginning of the stress period rather than events 
that might occur during the actual course of its business.
    OFHEO next considered whether it is appropriate to treat categories 
of operating expenses differently. OFHEO has determined that 
disaggregating the operating expenses into several categories would add 
needless complexity without providing any significant corresponding 
benefit to ensuring an Enterprise's capital adequacy. While some 
expense categories might reasonably be assumed to decline faster than 
the mortgage portfolio, some others might decline more slowly, and some 
might be expected to increase. OFHEO agrees with ACB and Freddie Mac 
that since operating expenses constitute a relatively small portion of 
an Enterprise's overall costs, they should not be subject to 
complicated modeling. Accordingly, OFHEO proposes to consider operating 
expenses in a single category rather than disaggregating them into 
distinct categories.
    Finally, OFHEO considered whether the operating expenses of each 
Enterprise should be modeled in the same manner. Freddie Mac 
recommended that instead of distinguishing between the Enterprises, the 
stress test should reduce operating expenses of each Enterprise in the 
same manner. Freddie Mac stated that any attempt to make fine 
distinctions between how each Enterprise might actually manage its 
operating expenses during the stress period could lead to extensive 
analysis that ought to have little affect on the overall capital 
requirement but, could increase the danger of different capital 
treatment for each Enterprise based on differences in accounting 
treatment of expenses.
    OFHEO agrees with Freddie Mac's recommendation not to distinguish 
between the Enterprises with respect to modeling operating expenses. A 
fundamental concept of the risk-based capital requirement is that the 
stress test establish a single set of rules that apply equally to both 
Enterprises. It would be inappropriate to establish a different stress 
test for each Enterprise. As a result, differences in operating 
expenses during the stress test between the Enterprises will reflect 
only differences in initial expense levels and mortgage portfolio 
composition, not any projected behavioral differences.

J. Dividends and Other Capital Distributions

1. Introduction
    The definition of a ``capital distribution'' in the 1992 Act 
includes the payment of common stock dividends, preferred stock 
dividends, and the repurchase or retirement of shares of stock.\186\ In 
recent years, both Enterprises have consistently paid significant 
amounts of dividends and have repurchased significant amounts of common 
stock.
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    \186\ 1992 Act, section 1303(2)(A) (12 U.S.C. 4502)(A)). The 
notable exception is the repurchase of shares for employee stock 
ownership programs under section 401 of the Internal Revenue Service 
Code of 1986.
---------------------------------------------------------------------------

    The 1992 Act directs OFHEO to consider dividends in the stress 
test. When an Enterprise makes a capital distribution and the amount of 
that distribution, however, are not specified in the 1992 Act. The only 
requirement is that dividends should be consistent with the stress test 
environment.\187\ Because capital distributions decrease equity, the 
more distributions an Enterprise makes during the stress test period 
(or during a real-life stressful environment), the more likely that an 
Enterprise will fail to meet its risk-based capital requirement.
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    \187\ 1992 Act, section 1361(b)(2) (12 U.S.C. 4611(b)(2)). 
``Characteristics of the stress period other than those specifically 
set forth in subsection (a), such as prepayment experience and 
dividend policies, will be those determined by the Director, on the 
basis of available information, to be most consistent with the 
stress period.''
---------------------------------------------------------------------------

2. Statutory Provisions
    The 1992 Act and the Charter Acts determine the authority of the 
Enterprises to make capital distributions.\188\ Under these statutes, 
an Enterprise may make a capital distribution without restriction when 
the Enterprise would remain adequately capitalized following the 
distribution.\189\ In all other circumstances, a capital distribution 
is prohibited outright or requires the approval from the Director of 
OFHEO.
---------------------------------------------------------------------------

    \188\ Fannie Mae's Charter Act and Freddie Mac's Corporation Act 
collectively are referred to as the ``Charter Acts.''
    \189\ In general, an Enterprise is considered ``adequately 
capitalized'' when it meets both the risk-based and minimum capital 
levels. It is ``undercapitalized'' when it does not meet the risk-
based capital level, but does meet the minimum capital level. It is 
``significantly undercapitalized'' when it does not meet either the 
risk-based capital level or the minimum capital level, but does meet 
the critical capital level. See section 1364 of the 1992 Act (12 
U.S.C. 4614), and section 303(c)(1) of the Charter Act and section 
303(b)(1) of the Corporation Act.
---------------------------------------------------------------------------

    Prior approval by the Director is required when an Enterprise is 
undercapitalized or if a capital distribution would cause the 
Enterprise to be undercapitalized.\190\ The legislative history of this 
requirement makes clear that, while approval in these circumstances can 
be granted, such approval ``should be the exception and not the rule.'' 
\191\ The Director's prior approval also is required when an Enterprise 
is significantly undercapitalized; however, the 1992 Act places 
conditions on the granting of such approval. In those circumstances, 
the Director may only approve a distribution if the Director determines 
that it will: (1) Enhance the Enterprise's ability to meet its capital 
requirements, (2) contribute to the Enterprise's long term safety and 
soundness, or (3) is otherwise in the public interest.\192\ No approval 
may be granted for a distribution that would cause the Enterprise to be 
significantly undercapitalized or critically undercapitalized.\193\
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    \190\ Section 303(c)(2) of the Charter Act and section 303(b)(2) 
of the Corporation Act.
    \191\ S. Rep. No. 102-282, at 24 (1992).
    \192\ 1992 Act, section 1366(a)(2) (12 U.S.C. 4616(a)(2)).
    \193\ 1992 Act, sections 1365(a)(2); 1366(a)(2)(A) (12 U.S.C. 
4615(a)(2); 4616(a)(2)(A)).
---------------------------------------------------------------------------

    This statutory structure draws a clear distinction between an 
Enterprise that fails to meet its risk-based requirement and one that 
fails to meet its minimum capital requirement. When an Enterprise fails 
to meet the risk-based capital requirement, the Director has full 
discretion to grant or deny approval for a capital distribution. 
However, when an Enterprise fails to meet the minimum capital 
requirement, the Director's discretion is limited. Moreover, the 
Director is prohibited from approving a distribution that would cause 
the Enterprise to fail to meet the minimum capital requirement.
3. Proposed Approach
    The proposed regulation provides that during the stress period:
     When paid, dividends are paid at rates consistent with 
historical experience;
     Dividends are paid on common stock when the Enterprise 
meets the risk-based capital requirement and the minimum capital 
requirement;
     Dividends are paid on preferred stock when the Enterprise 
meets the minimum capital requirement; and
     No dividends are paid when the Enterprise does not meet or 
would not

[[Page 18170]]

after payment of the dividend meet the minimum capital requirement.
    In making this proposal, OFHEO emphasizes that there are 
significant differences between establishing a dividend payment policy 
for the risk-based capital requirement and acting on a dividend 
approval request from an Enterprise that is no longer adequately 
capitalized. Accordingly, provisions of the stress test which provide 
for the payment of dividends by an undercapitalized Enterprise in some 
circumstances and not others should not be interpreted as an indication 
of how OFHEO will act on any specific dividend approval request. In 
practice, OFHEO will evaluate any request for approval of a dividend 
payment on the basis of a case-by-case analysis of all the relevant 
facts and circumstances.
a. Preferred Stock
    Under the proposed regulation, dividends are paid on preferred 
stock during the stress period when the Enterprise meets its estimated 
minimum capital requirement. Preferred stock dividends are based on the 
coupon rates of the issues outstanding. The coupon rates for any issue 
of variable rate preferred stock is calculated using projections of the 
appropriate index rate.
    To determine whether the Enterprise meets the minimum capital 
requirement, the stress test computes the minimum capital level each 
month by applying the appropriate leverage ratios to all assets (2.50 
percent) and off-balance sheet obligations (0.45 percent). OFHEO notes 
that interest rate and other off-balance sheet contracts also affect 
the minimum capital number.\194\ However, incorporating these features 
in the calculation would require OFHEO to compute the credit equivalent 
amount of interest rate and foreign exchange contracts, which would add 
unnecessary complexity but provide little corresponding benefit. 
Accordingly, for purposes of determining dividend payouts in the stress 
test, OFHEO believes that the approach described above provides a 
reasonable approximation of the minimum capital calculation.
---------------------------------------------------------------------------

    \194\ 12 CFR 1750.4.
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    As noted above, preferred stock dividends are paid in some 
circumstances in which common stock dividends are not paid. The stress 
test includes this distinction based on the recognition that when a 
corporation issues preferred stock, it is making a higher level of 
commitment to those investors than when it issues common stock. 
Preferred stockholders have a first claim on distributions. Therefore, 
failure to pay dividends on both classes of stock likely would have 
greater repercussions on an Enterprise's funding costs and ability to 
attract new equity capital than would a failure to pay common stock 
dividends while preferred stock dividends were maintained. Accordingly, 
when an Enterprise is classified as undercapitalized, the stress test 
pays preferred stock dividends, but not common stock dividends.
b. Common Stock
    Under the proposed regulation, dividends are paid on common stock 
during the first four quarters of the stress period. The stress test 
specifies that common stock dividends cease after that, reflecting the 
strong likelihood that an Enterprise would not meet the risk-based 
capital requirement during the final nine years of the stress period. 
The rate at which dividends are paid is based on the trend in the 
Enterprise's earnings. If earnings are positive and increasing, 
dividends are paid based at the same dividend payout ratio as the 
average payout ratio of the four quarters preceding the stress test. 
Otherwise, dividends are paid based at the preceding quarter's dollar 
amount of dividends per share. Dividends would be cut off before the 
end of the first year if an Enterprise failed to meet its estimated 
minimum capital requirement.
    OFHEO believes this rule is based on a reasonable representation of 
when an Enterprise will no longer be adequately capitalized. The 
conditions of the stress test are sufficiently stressful to assure that 
the Enterprise would be undercapitalized by the end of the first year 
of the stress period. By that time, an Enterprise's portfolio would 
have been subjected to very large interest rate increases or decreases. 
If, at that point, it was subjected to those same large increases, 
i.e., a total of up to 1200 basis points over two years, it is 
reasonable to assume that the Enterprise would be undercapitalized. The 
Enterprise would have to withstand more severe credit losses because 
the hypothetical stress tests would also compound declines in house 
prices associated with the actual stress test. Estimating with greater 
accuracy whether an Enterprise would meet its risk-based capital 
requirement at any time during the stress period is inherently 
difficult. This would require simulating a series of hypothetical ten-
year stress tests, the last of which would involve generating cash 
flows extending ten years beyond the end of the actual stress period. 
This would add great technical complexity to the stress test without 
providing any meaningful benefit.
c. Other Types of Capital Distributions
    The proposed regulation does not provide for any other types of 
capital distributions, such as repurchases of common stock, or 
redemption of preferred stock. Although the Enterprises have both 
repurchased a significant number of shares of their own common stock in 
the past several years, the stock buybacks were irregular events based 
on the current share price, expected return on potential investments, 
and the profitability of each Enterprise. The Enterprises have made no 
firm commitment to investors to continue share repurchases. 
Furthermore, OFHEO believes that the stress test environment would not 
be conducive to share repurchases.
4. Analysis of ANPR Comments
    In response to questions in the ANPR, Freddie Mac emphasized that 
any assumptions that OFHEO makes regarding dividend payments must be 
consistent with the 1992 Act, particularly the provisions related to 
how capital classifications affect dividend payments. With regard to 
preferred stock dividends, Freddie Mac recommended that OFHEO assume 
that an Enterprise pays dividends on such stock so long as it satisfies 
its minimum capital requirement and discontinues preferred dividends 
thereafter. With regard to common stock dividends, Freddie Mac 
recommended that OFHEO assume that an Enterprise pays a constant 
dividend payout ratio on common stock until earnings become negative, 
at which time common stock dividends would be discontinued.
    The proposed regulation, which ties dividend payouts to capital 
classifications, is consistent with the 1992 Act and is generally 
consistent with Freddie Mac's recommendations. More specifically, OFHEO 
agrees with Freddie Mac's recommended approach for paying preferred 
stock dividends until an Enterprise's capital falls below the minimum 
level. OFHEO believes this treatment of preferred stock dividends 
properly reflects the high level of commitment of the Enterprises to 
investors in their preferred stock.
    In addition, eliminating common stock dividends after an Enterprise 
becomes undercapitalized is roughly equivalent to Freddie Mac's 
recommendation to cut off common stock dividends when an Enterprise's 
earnings turn negative. However, while Freddie Mac would reduce 
dividends proportionately if earnings decline, the proposed regulation 
provides for the

[[Page 18171]]

payment of a constant dollar amount. OFHEO believes the payout rule in 
the stress test appropriately reflects the current dividend payout 
history of the Enterprises. Both Enterprises have made fairly strong 
commitments to investors regarding dividend payouts, and have been slow 
to lower their dividend payments in the face of declines in earnings.
    ACB recommended that dividends be suspended immediately in the 
stress test, since the Enterprises are assumed to be in a wind down and 
shareholders would be strictly residual claimants. ACB's recommendation 
to suspend all dividends immediately is not consistent with the 
apparent intent of the 1992 Act, which specifically mentions dividend 
policies and directs OFHEO to consider dividend policies that would be 
``most consistent with the stress period.''\195\ As discussed above, 
OFHEO believes that the proposed capital distribution rule is 
consistent with the stress test period. Furthermore, the stress test 
would fail to incorporate a likely source of capital depletion that 
would affect an Enterprise in a real-life stressful environment if all 
capital distributions were eliminated during the entire stress test 
period.
---------------------------------------------------------------------------

    \195\ 1992 Act, section 1361(b)(2) (12 U.S.C. 4611(b)(2)).
---------------------------------------------------------------------------

    ACB's comment that shareholders would be strictly residual 
claimants, which implies that the stress test is a liquidation 
situation, is not consistent with the concepts underlying the stress 
test. A wind down or ``no new business'' stress test is not the 
equivalent of a liquidation. Rather, it is a test of how much capital 
an Enterprise would need to survive.

K. Other Off-Balance Sheet Guarantees

    In addition to guaranteeing mortgage-backed securities they issue 
as part of their mainline business, the Enterprises occasionally 
guarantee other securities. Such guarantees are referred to as ``other 
off-balance sheet (OBS) guarantees.'' Examples of other OBS guarantees 
include guarantees of tax-exempt multifamily housing bonds issued by 
state and local government agencies, Enterprise-issued whole loan REMIC 
securities to security, and private label (non-GSE-or GNMA-issued) 
REMIC securities. In general, an Enterprise's guarantee is protected by 
other credit enhancements, including reserve funds, insurance 
arrangements, and/or subordinated security tranches.
    For the following reasons it is not now feasible to simulate the 
detailed financial impact on an Enterprise of other OBS guarantees over 
the 120 months of the stress period. First, the mortgage collateral for 
such securities is often dissimilar from the Enterprise's mortgages on 
which the stress test's mortgage performance models are based. Second, 
current data on the status of the underlying collateral is difficult to 
obtain. Third, the structures of the securities and the nature of 
credit enhancements vary, requiring the individual modeling of each 
guaranteed security, which would, at this time, require an inordinate 
amount of resources.
    The stress test utilizes a proxy for the detailed modeling of the 
impact of other OBS guarantees on the amount of starting capital that 
an Enterprise would need to just maintain positive capital during the 
stress period. The proxy treatment consists of multiplying the 
outstanding balance of all other guarantees at the beginning of the 
stress period by .0045, and adding the result to the amount of starting 
capital calculated for all other aspects of an Enterprise's operations. 
The multiple .0045 corresponds to the minimum capital requirement 
associated with these other OBS guarantees.

L. Calculation of the Risk-Based Capital Requirement

1. Proposed Approach to Calculating Capital
    The 1992 Act requires an Enterprise to meet the risk-based capital 
requirement. To determine this requirement, the statute establishes a 
two-step process. The first step is to determine the amount of capital 
that an Enterprise needs to just maintain positive capital during a 
ten-year period of economic stress. The second step is to increase that 
amount of capital by another 30 percent to capture management and 
operations risk.
    OFHEO proposes to use a present value approach to calculate the 
capital that an Enterprise needs to just maintain positive capital 
during the stress test. Once the stress test has projected the capital 
of an Enterprise at the end of every month in the stress period, the 
capital calculation process discounts the monthly capital balances back 
to the start date of the stress period. The Enterprise's starting 
capital is then adjusted by subtracting the lowest of the discounted 
capital balances to account for the smallest capital excess or largest 
deficit (subtracting a negative number in the case of a deficit). The 
discount factor used to discount a monthly capital balance is based on 
after-tax borrowing or investing yields (as appropriate) for that month 
and all previous months during the stress period.
    After the stress test ascertains the amount of capital necessary to 
just maintain positive capital during the stress test, it then 
multiplies that amount by 1.3 to arrive at the risk-based capital 
requirement.
2. Justification for Using a Present Value Approach
    The 1992 Act requires OFHEO to determine the amount of capital that 
is sufficient for an Enterprise to just maintain positive capital 
during the ten-year stress period. However, when an Enterprise has more 
(or less) capital than it needs to just maintain positive capital, the 
law does not specify the procedure for calculating how much capital it 
would need to just maintain positive capital.
    In analyzing the best method to calculate capital during the ten-
year stress period, OFHEO considered two approaches: (a) the present 
value approach, described above, and (b) an ``iterative approach'' in 
which the stress test would be run multiple times with hypothetical 
adjustments made to each Enterprise's balance sheet prior to each run. 
The present value approach more efficiently produces results comparable 
to the iterative approach. Both approaches recognize that a dollar 
today is worth significantly more than a dollar ten years from now, 
because the dollar can be invested so as to return more in a later 
year.
    Under the iterative approach, the capital calculation process 
begins by running the stress test on the basis of an Enterprise's 
actual assets, liabilities, net worth, and off-balance sheet items as 
of a given date. The first stress test run would be used to identify 
the lowest capital balance that the Enterprise has during the stress 
period. Then, based on that result, adjustments would be made to the 
starting capital and the assets and/or liabilities on the Enterprise's 
balance sheet. The goal of these adjustments is to construct a starting 
position book of business that, when subject to the stress test, will 
result in the Enterprise just maintaining positive capital during the 
stress test. If a run results in the Enterprise's capital reaching a 
minimum point greater than zero, OFHEO would reduce the starting 
capital in order to move the minimum point down toward zero in the next 
run. If a run resulted in the Enterprise's capital reaching a minimum 
point less than zero, then OFHEO would increase the starting capital in 
order to move the minimum point up toward zero in the next run. If the 
second run did not achieve the desired result, successive runs would be 
made following further

[[Page 18172]]

adjustments to the starting position balances.
    OFHEO is proposing the present value approach rather than the 
iterative one based on the following considerations. The present value 
approach is comparatively simple and easy. It will not require explicit 
changes to an Enterprise's actual assets, liabilities, net worth, and 
off-balance sheet items as they exist at the start of the stress test, 
and it achieves results comparable to the iterative approach. It 
achieves these results because the discount factors used in the present 
value calculations, which calculate the surplus or deficit of starting 
capital, are consistent with the effects during the stress period of 
the balance sheet adjustments required by the iterative approach. The 
discount factors reflect the yields on additional debt or investments 
offsetting necessary changes in starting capital. For example, consider 
a scenario in which an Enterprise holds more starting capital than 
necessary to maintain positive capital throughout the stress period. 
Balance sheet adjustments made for the final iteration would likely 
involve substituting for the surplus starting capital an equal amount 
of debt. Discounting the appropriate monthly capital balance during the 
stress period, using stress period yields, results in a comparable 
amount.
    Based on these considerations, the present value approach would be 
a more appropriate methodology for carrying out the purposes of the 
statute. The iterative approach would add needless complexity and 
require OFHEO to make changes to the balance sheets of the Enterprises. 
Each iterative run, would be based on hypothetical representations of 
the Enterprise's position. The present value approach eliminates the 
need for these artificial adjustments and the unwarranted complexity 
that the iterative approach's adjustment process would entail.
    Under the present value approach, it is necessary to determine the 
appropriate monthly discount rates. In determining the monthly rates, 
OFHEO sought a set of discount rates that would reflect the time value 
of money to an Enterprise during the stress period. Accordingly, the 
discount rates applied in the stress test are computed as an after-tax 
rate. Such an after-tax rate reflects the fact that any borrowing 
necessary to fund an Enterprise's business activities would be 
deductible for income tax purposes. Conversely, any additional earnings 
would be subject to income taxes.
    These discount rates are intended to reflect the fact that interest 
rates will differ dramatically between the rising and falling rate 
scenarios and at given times in each scenario. When an Enterprise is 
borrowing new funds during the stress period, the marginal effect that 
a change in its cash position in one month will have on its equity in a 
subsequent month will be reflected by its after-tax cost of borrowing 
during the intervening period. Alternatively, if the Enterprise is a 
net investor in a given month, the marginal effect is reflected by its 
after-tax earnings on new investments in Treasury bills.
    This discounting procedure will reasonably relate changes in 
capital to changes in an Enterprise's risk position. For example, if an 
Enterprise were to take an incremental risk position that resulted in 
an incremental loss during the first month of the stress period, that 
loss would compound during the stress period at the Enterprise's after-
tax borrowing or investment rate. If an Enterprise is borrowing, this 
one month's incremental additional loss would require additional 
borrowings during the balance of the stress period. These additional 
borrowings would create additional interest payments for which further 
borrowing would be required. If the Enterprise is investing, the loss 
would leave smaller amounts to be invested, which would earn less 
interest. After applying the discount factors, the change in each 
future month's capital would equal the initial loss. Thus, the change 
in the estimated amount of the first month's incremental capital needed 
to just maintain positive capital during the stress test would also 
equal that initial loss. More generally, if a new asset were to 
generate a stream of losses over the course of the stress period, the 
amount of starting capital needed would rise by the present value of 
this stream of losses.

IV. Technical Supplement

A. Purpose and Scope

    This technical supplement provides detail on the specification and 
estimation of statistical (econometric) models for mortgage 
performance, and how those statistical models are applied in the 
proposed risk-based-capital stress test. The supplement focus is on 
technical aspects of the statistical modeling. This focus includes: 
theoretical considerations, sources and uses of historical data, 
functional forms for statistical models, development of explanatory 
variables for the statistical analyses, results of statistical model 
estimations, and application of the resulting statistical equations to 
predict mortgage performance in the stress test. Each of the following 
parts of this supplement covers these elements for its respective part 
of mortgage performance. The topic areas covered here are:
     Single Family Default/Prepayment,
     Single Family Loss Severity,
     Multifamily Default/Prepayment,
     Multifamily Loss Severity, and
     Property Valuation.
    An additional, and important component of this Supplement is the 
description of how the statistical models of mortgage performance are 
reasonably related to the benchmark loss experience (BLE) identified in 
NPR1. The first way in which OFHEO reasonably relates the mortgage 
performance component of the stress test to the BLE is through 
application of housing market conditions that represent the conditions 
of that experience. Those conditions include house price growth rates, 
rent growth rates, and rental vacancy rates. The next part of this 
supplement, Property Valuation, details how OFHEO developed these 
variables for use in the stress test. How these variables are actually 
used in the stress test is covered in the section 3.5, Mortgage 
Performance, of the Regulation Appendix, although some general 
information is provided here.
    The second way in which mortgage performance in general, and credit 
losses in particular, are related to the BLE is through calibration 
mechanisms that adjust statistically derived equations to match the 
actual loss rates of the BLE. These adjustments are required because 
the statistical equations are estimated over a wide range of data, of 
which the benchmark experience is only a small part. To reasonably 
relate mortgage losses to the BLE, the stress test imposes housing 
market conditions from the time and place of the BLE. In addition, the 
stress test adjusts defaults and severities by factors that cause the 
test to replicate critical aspects of the BLE when the statistical 
models are applied to benchmark loans. The methods of deriving these 
calibration adjustment factors are described in the Single Family 
Default/Prepayment and Single Family Loss Severity parts of this 
Supplement.

B. Single Family Default/Prepayment

1. Introduction
    To develop the stress test model of single family default and 
prepayment rates, OFHEO analyzed the historical experience of 
Enterprise single family loans from 1979 through 1995. This experience 
is defined by an econometric model in which probabilities of default 
and prepayment in each time period are

[[Page 18173]]

determined jointly using a multinomial logit specification. The 
theoretical foundation used for choosing variables to use in the model 
is financial options theory. This is the predominant theory used in 
mortgage performance research. It suggests that borrowers make choices 
regarding maintaining or terminating mortgages based upon the relative 
financial value of those choices. In this context, each borrower has 
the choice, in each time period, to make the payment and maintain the 
mortgage, pay off the mortgage in full (a prepayment), or stop making 
payments and default.
    Owing to the large amount of data available to estimate this model, 
OFHEO chose techniques that captured the essence of individual borrower 
choice, consistent with efficient use of computer resources. These 
techniques start with estimating separate sets of default and 
prepayment equations for fixed-rate mortgages (FRMs) and for 
adjustable-rate mortgages (ARMs).\196\ A third set of equations was 
estimated to project the performance of less-prevalent single family 
loan types relative to the dominant 30-year fixed-rate mortgages. The 
second method of capturing borrower choice characteristics while 
limiting computer resources was to use random samples of fixed-rate 
loan products, rather than attempting to estimate the model on all 
loans ever purchased by the Enterprises. The third method was to use 
quarters rather than months as the observation time period. This time 
period is important because each loan enters the analysis in the form 
of an event history: every time period for which the loan was active 
provides an observation for the statistical analysis. Using quarters 
reduces the number of observations used in the statistical analysis 
without losing any essential detail regarding borrower choices. The 
last method of maintaining the quality of individual loan analysis 
while limiting computer resources was to use a weighted regression 
scheme, so that all loans do not need to enter the analysis 
individually. All loans with the same characteristics are treated as 
one loan, with the actual number of loans with those characteristics 
used as a weighting factor.
---------------------------------------------------------------------------

    \196\ In this model, ARMs include all mortgages that have 
variable payment features.
---------------------------------------------------------------------------

    The equations that result from the statistical analysis were 
adjusted or calibrated to the BLE before use in the stress test. The 
calibration procedure adjusts the default equations so that if the 
actual benchmark loans (as defined in NPR1) were input into the 
equations, with benchmark house price growth rates and interest rates, 
the resulting 10-year cumulative default rate would identically match 
that of the BLE (14.9 percent).
    The remainder of this supplementary material is organized as 
follows: Section 2 provides a summary of the conceptual framework 
underlying the estimation of the statistical model of single family 
mortgage default and prepayment. Section 3 describes the loan level 
data used in the empirical analysis. Section 4 outlines the general 
approach to the statistical analysis of default and prepayment events, 
based on the application of the multinomial logit model. Section 5 
defines the explanatory variables used in that analysis. The empirical 
results are presented in section 6, which is followed in section 7 by a 
discussion of the application of the estimated default and prepayment 
equations in the stress test. Section 8 ends this supplementary 
material by describing how the estimated model is used in the stress 
test to produce results consistent with the BLE.
2. Conceptual Framework
    Financial options theory is the most widely accepted theoretical 
framework for the analysis of residential mortgage default and 
prepayment. This framework hypothesizes that mortgage borrowers will 
exercise embedded call (prepayment) or put (default) options when 
either of these alternatives becomes financially optimal. The financial 
options theory assumes that an individual mortgage borrower can 
increase his lifetime wealth by defaulting on a mortgage when the 
market value of the mortgage exceeds the market value of the house, 
implying a direct empirical link between changes in housing values, 
borrower equity, and the decision to default. Likewise, the option to 
refinance the mortgage when market rates fall below the current rate on 
the mortgage provides a means for borrowers to increase their wealth by 
prepaying, and links observed prepayment behavior to changes in 
interest rates.\197\
---------------------------------------------------------------------------

    \197\ There may also be secondary effects of borrower equity on 
prepayment, and of interest rates on default. For example, attempts 
by borrowers to prepay their mortgages may be frustrated due to 
declining house prices and failure to qualify for refinancing. On 
the other hand, borrowers in a negative equity position may be 
reluctant to default if they have current mortgage coupon rates that 
are less than the prevailing market rate of interest. In this second 
case, the asset value of the low interest rate mortgage would be 
foregone if the put option is exercised and the borrower defaults. 
However, the empirical significance of mortgage value for default is 
questionable given the inability of borrowers to trade on this 
asset, other than by selling the property and taking back a mortgage 
at a rate between the original note rate and the current market 
rate. This option is precluded by the ``due-on-sale'' provisions of 
most residential mortgage contracts. The extent to which this option 
is used informally is unknown.
---------------------------------------------------------------------------

    Previous empirical studies on mortgage terminations have provided 
empirical support for the options theory, as various approximations to 
the financial values of the options have been found to be strongly 
associated with observed default and prepayment outcomes.\198\ However, 
some of the same studies also indicate that borrowers do not behave in 
the ``ruthless'' manner suggested by the pure options theory. These 
empirical studies vary in the degree to which the full implications of 
the theory are incorporated, mainly due to limitations on the available 
data and the ability to measure or impute options values to individual 
borrowers.
---------------------------------------------------------------------------

    \198\ Examples of empirical models based on the options 
framework include: Dunn and McConnell (1981), Foster and Van Order 
(1984, 1985), Buser and Hendershott (1984), Brennan and Schwartz 
(1985), Kau, Keenan, Muller, and Epperson (1985, 1990), and 
Hendershott and Van Order (1987).
---------------------------------------------------------------------------

    The measurement of borrower equity has been addressed in 
essentially two ways in the academic literature. One approach employs 
stochastic simulations to impute aggregate distributions of properties 
with positive or negative equity, while simultaneously accounting for 
the impact of default and prepayment events on these distributions. 
This is the approach used by Foster and Van Order (1984, 1985). Another 
approach, adopted in recent work by Deng, Quigley, and Van Order (1996) 
and Deng (1997), has been to combine mathematical assumptions about the 
diffusion of housing values with loan-level data to assign ``ex ante'' 
probabilities of negative equity to individual properties.\199\ Both 
approaches are generally consistent with the assumptions of the option 
theory, and they differ mainly in their application to aggregate versus 
loan-level data.
---------------------------------------------------------------------------

    \199\ Probabilities assigned in this way are ``ex ante'' because 
they depend only on information about individual mortgages available 
at origination and subsequent changes in the mean (drift) and 
variance (volatility) of house price appreciation rates. No 
information on the incidence of default or prepayment among other 
loans is used to adjust the projected distribution of housing values 
used to assign probabilities of negative or positive equity to loans 
that remain active.
---------------------------------------------------------------------------

    In recent years, a consensus seems to have emerged among 
practitioners that the option values, to the degree that they can be 
measured, remain important for predicting default and prepayment,

[[Page 18174]]

but provide only necessary, rather than sufficient, conditions. For 
example, in the case of mortgage default, negative equity alone may not 
be sufficient to induce a borrower to default, but given some other 
``trigger event,'' such as job loss or marital disruption, the decision 
to default would then depend on whether equity was positive or 
negative. In the case of prepayment, borrowers who would otherwise 
appear to have a financial incentive to refinance (prepay) to obtain a 
lower interest rate, may not wish to incur the associated transactions 
costs given their expected time horizons for occupying the home.
    While the option theory succeeds as a general framework, empirical 
models of mortgage default and prepayment must be flexible enough to 
account for variation in mortgage performance that may not appear to be 
fully consistent with optimal behavior, such as borrowers defaulting 
when house prices are increasing or prepaying when interest rates are 
increasing. The empirical model must account for limitations on the 
information available to compute the exact values of embedded options 
for individual borrowers. In addition, a wide variety of loan 
characteristics must also be accounted for, which has led to the 
widespread application of what are generally referred to as ``options-
based'' empirical models, such as those cited above. The models applied 
in the stress test are typical of those that use the options-based 
approach.
3. Data
    OFHEO obtained loan-level information on previous Enterprise single 
family mortgage originations and used these data to estimate models of 
mortgage performance. The data included information on the origination 
characteristics of mortgages, information on last-paid installment 
dates, and loan status outcomes from the Enterprise loan-tracking 
systems. This information allowed OFHEO to reconstruct ``event 
histories'' of the period-by-period performance of individual loans, 
from the date of origination to either the point where the loan 
terminated or the end of the sample period. OFHEO combined loan-level 
information from both Enterprises to develop its own data files for 
statistical analysis. Standardized or ``normalized'' data files were 
constructed to assure similar content and structure across 
Enterprises.\200\
---------------------------------------------------------------------------

    \200\ The process of data normalization involved confirming the 
consistency of mortgage product types and loan characteristics and 
defining standardized data fields.
---------------------------------------------------------------------------

    The options theory views mortgage default and prepayment events in 
terms of decisions by individual borrowers to terminate their loans. 
This view has implications for the way mortgage outcomes and their 
associated probabilities are specified in the statistical analysis. 
Default and prepayment are specified to occur in the month following 
the date of the last-paid-installment. After mortgage prepayment, the 
Enterprises are likely to update the loan status almost immediately. By 
contrast, due to the varying length of the mortgage foreclosure 
process, the Enterprises may not classify defaulting loans as defaults 
until some months after the last-paid-installment date. However, in the 
model, the default event is nevertheless considered to have occurred at 
the point the borrower ceases payment on the loan.\201\ The event 
history used for that loan ends at that point in time. The data used in 
the statistical analysis included mortgage originations for the period 
from January 1979 to December 1993, with mortgage performance measured 
through December 1995. Therefore, these data provided a minimum of two 
years of loan experience for the most recent origination cohorts.\202\
---------------------------------------------------------------------------

    \201\ At the time that data bases were constructed for this 
analysis, information was not available from Freddie Mac on last-
paid-installment dates. Therefore, OFHEO used the ``closing date'' 
for Freddie Mac's defaulted loans. This is the date of disposition 
of a foreclosed property. The last-paid-installment date was used 
for Fannie Mae defaults.
    \202\ Note that for some loans the last-paid-installment will 
occur prior to the end of the sample, with no corresponding change 
in loan status from active to defaulted. These ``censored'' events 
were treated in the same manner as loans that remained active 
through the end of the sample period. That is, they are viewed as 
active up to and including the last quarter in the sample period. 
Note that these censored default events do not occur in sufficient 
numbers to have a material impact on the statistical estimates. One 
reason is that during those time periods and places in which the 
incidence of default was greatest, such as, for example, in the 
historical benchmark experience, foreclosure and changes in loan 
status occurred within several months of the last payment by the 
borrower. In addition, relatively complete loan histories are 
available for those loan origination cohorts among which the 
majority of default events occurred on Enterprise loans. While more 
recent cohorts with shorter event histories have greater potential 
for censoring of default events, the impact of censoring on the 
statistical estimates is negligible because default rates have been 
so low in recent years.
---------------------------------------------------------------------------

    Ideally, models would be estimated using contemporaneous values of 
factors predictive of default and prepayment during each period a loan 
is outstanding. Although this type of ``panel'' data does not exist for 
historical Enterprise loan records, it was possible to reconstruct 
historical data on key determinants of default and prepayment, such as 
house prices and interest rates, and add this information to the 
individual loan event histories. Using these histories, OFHEO was able 
to estimate dynamic models for default and prepayment. The models are 
``dynamic'' in the sense that OFHEO can estimate and simulate mortgage 
performance in response to actual or hypothetical (e.g., stress test) 
changes in economic circumstances over time.
4. Specification of the Statistical Model
    The proposed regulation employs a monthly cash flow model of 
Enterprise performance over a ten-year stress period. The simulation of 
mortgage cash flows requires conditional rates of default and 
prepayment to be applied to outstanding mortgage balances during each 
month of the stress test. The purpose of the models described in this 
technical supplement is to provide a means of generating the required 
termination rates in a manner that is reasonable for Enterprise loans 
under the circumstances of the stress period.
    Conditional rates of default and prepayment vary depending on a 
variety of factors, both random and systematic, some of which are fixed 
at origination and others that vary over time. Characteristics of loans 
and borrowers at origination can affect the level and timing of 
mortgage default and prepayment throughout the life of the loan. For 
example, conditional default and prepayment rates exhibit 
characteristic age-profiles that increase during the first years 
following origination, peak sometime between the fourth and seventh 
years, and decline gradually over the remaining years.\203\ Default and 
prepayment rates also vary systematically in response to economic 
circumstances and other factors over time, such as changes in house 
prices and interest rates that affect the value to the borrower of 
embedded options.
---------------------------------------------------------------------------

    \203\ See discussion in Schwartz and Torous, at 379 (1989).
---------------------------------------------------------------------------

    Like other time-or age-dependent processes, mortgage terminations 
are highly amenable to analysis using statistical survival-time models 
specified in terms of conditional probabilities of prepayment and 
default. Default and prepayment are ``competing risks,'' which means 
that the occurrence of one type of event precludes the chance to 
observe when the other event might have occurred, and vice versa. In 
such a case it is necessary to account for the joint mathematical and 
statistical dependence of the conditional probabilities of default and 
prepayment on each other. Failure to account for the competing-risks 
nature of the events can lead to projections of total termination

[[Page 18175]]

rates (default plus prepayment) that are mathematically inconsistent 
and that would preclude their application in the type of actuarial 
calculations of cash flows required for the stress test.
    As outlined above, mortgage default and prepayment result in an 
observed last-paid-installment, after which no further payments are 
forthcoming. Thus, for loans outstanding at the beginning of each time 
period, three mutually exclusive outcomes are possible in the model: 
(1) the borrower defaults; (2) the borrower prepays the loan in full; 
or (3) the borrower makes the scheduled loan payment, and the loan 
remains active and part of the event history sample for the next time 
period. For the purposes of the statistical analysis, each of these 
outcomes is interpreted as an ``event.'' This approach implies that 
each loan contributes potentially many observations to the event 
history sample, depending on how long it remains active before 
experiencing one of the terminal events or reaching the end of the 
sample period.
a. Multinomial Logit Models
    OFHEO has estimated multinomial logit models for quarterly 
conditional probabilities of default and prepayment.\204\ Several 
empirical studies have applied some form of the logit or similar 
qualitative response models to analyze mortgage prepayment and default 
behavior.\205\ The corresponding mathematical expressions for the 
conditional probabilities of default (D(t)), 
prepayment (p(t)), or remaining active 
(A(t)) over the time interval from t to t + 1 are 
given by:
[GRAPHIC] [TIFF OMITTED] TP13AP99.001

[GRAPHIC] [TIFF OMITTED] TP13AP99.002

[GRAPHIC] [TIFF OMITTED] TP13AP99.003

    Constant terms D and p, and 
coefficient vectors D and p, 
are the unknown parameters that must be estimated. XD(t) is 
a vector of mostly time dependent explanatory variables that are 
assumed to influence directly the conditional probability of defaulting 
(versus remaining active), and Xp(t) is a vector of mostly 
time dependent explanatory variables assumed to influence directly the 
conditional probability of prepaying (versus remaining active).\206\ 
The probability of remaining active (A(t)) is equal 
to 1 minus the other two probabilities, so that the three probabilities 
sum to 1.
    The probabilities and coefficient vectors have a convenient 
interpretation when expressed in terms of odds ratios:
[GRAPHIC] [TIFF OMITTED] TP13AP99.004

[GRAPHIC] [TIFF OMITTED] TP13AP99.005

    These expressions imply that the percentage impact of a one-unit 
change in an element of XD(t) on the relative probability or 
odds of defaulting versus remaining active is given by the 
corresponding element of the coefficient vector, D. 
A similar result holds for prepayment. Note also, that while changes in 
variables that affect the probability of prepayment affect the absolute 
level of the probability of default, and vice versa, such changes 
affect the probability of remaining active in a symmetric manner, so 
that the ``odds'' of defaulting versus remaining active are not 
affected.\207\
---------------------------------------------------------------------------

    \204\ The decision to model default and prepayment as quarterly 
events was consistent with the application of quarterly house price 
indexes in computing the underlying distributions of borrower 
equity. The resulting quarterly default and prepayment probabilities 
were converted to monthly factors for input to the monthly cash flow 
calculations required for application in the stress test.
    \205\ Examples of previous applications of the logit model are 
Campbell and Dietrich (1983), Zorn and Lea (1989), and Cunningham 
and Capone (1990).
    \206\ Some elements of XD(t) and Xp(t) are 
constant over the life of the loan and are not functions of t.
    \207\ The multinomial logit model is widely applied in the 
analysis of consumer choice among discrete alternatives, where this 
feature has been called the ``independence of irrelevant 
alternatives.'' In the context of consumer choice theory this 
independence can result in apparent anomalies when close substitutes 
to existing choices are introduced. See, for example, McFadden 
(1976). This issue does not arise in the present context.

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[[Page 18176]]

b. Estimation of Multinomial Logit Coefficients
    The multinomial logit specification given by equations (1)-(3) is a 
purely mathematical representation of the underlying probabilities. How 
the unknown parameter coefficients of the logit model are estimated 
statistically depends on whether the model is applied to individual or 
aggregate data. Under some circumstances, the two approaches are 
mathematically equivalent. However, in some situations, the use of 
aggregate data may entail considerable loss of information.\208\
---------------------------------------------------------------------------

    \208\ For example, if the data are aggregated by taking average 
values of the explanatory variables within broad product groupings, 
then particular combinations of explanatory variables that exist for 
individual loans and which are associated with significant 
differences in probabilities of default and prepayment, will not be 
represented in the data. While this may not matter under ``normal'' 
circumstances, it could limit the usefulness of the model in 
projecting rates of default and prepayment within high risk 
categories under circumstances different than those embodied in the 
original aggregation scheme, such as those of the stress test.
---------------------------------------------------------------------------

    If only aggregate data were used, the proportions of loans 
defaulting, prepaying, and remaining active would be used to estimate 
the unknown coefficients D, p, 
D, and p directly by replacing 
the probabilities in equations (4) and (5) with the corresponding 
observed sample proportions and applying ordinary least squares. In 
this case the explanatory variables XD(t) and 
Xp(t) correspond to the characteristics of the groups or 
classes of loans used in tabulating the observed sample proportions.
    When loan-level data are available, it is possible to use equations 
(1)-(3) as an exact mathematical representation of the probabilities of 
individual loan events. In this case, estimation of unknown 
coefficients is achieved by the method of maximum likelihood. This 
approach chooses the values of D, 
D, p, and p 
that maximize the joint likelihood or probability of the entire event-
history sample having actually occurred. For example, the joint sample 
likelihood is the product of the probabilities of each of the 
independent loan event observations:
[GRAPHIC] [TIFF OMITTED] TP13AP99.006

where for each observation i = 1,2. . ., N, Pt is the 
estimated probability that the event that is actually observed would 
have occurred. These probabilities are obtained by substituting the 
appropriate expression from equations (1)-(3) for Pi in 
equation (6). The solution is found by varying the values of the 
elements of D, D, 
p, and p until the joint 
probability reaches its maximum value. The final values of 
D, D, p, 
and p are the maximum likelihood estimates. 
Numerous statistical software packages exist for this purpose.
    The approach adopted by OFHEO is based on loan-level data, which 
has the significant advantage of preserving as much detail as possible 
on individual loan circumstances. This approach results in a flexible 
description of loan behavior, which can be used to project mortgage 
performance under the abnormal scenarios of the proposed regulation.
5. Explanatory Variables for Default and Prepayment
    OFHEO estimated three separate sets of multinomial logit 
probability equations. The primary default and prepayment equations are 
for single family, 30-year FRMs. These loans comprise about 80 percent 
of all single family loans in the historical data obtained from the 
Enterprises. A second set of equations was estimated solely on data for 
ARMs. All loan types with any potential payment adjustments throughout 
the life of the loan were included as ARMs for purposes of the 
statistical estimation. A third set of default and prepayment equations 
was estimated to project the performance of less-prevalent single 
family loan types relative to 30-year fixed-rate mortgages. This 
estimation was performed using data on 30-year FRMs and all other 
fixed-rate loan types (including balloons). These loan types were 
grouped as: 20-year FRM, 15-year FRM, balloon, FHA/VA, and second 
liens. Data on 30-year FRMs are included in the estimation sample 
because the number of observations on other, less popular fixed-rate 
mortgage types was insufficient for estimating product-specific default 
and prepayment equations. However, the resulting default and prepayment 
equations are only used to project performance of the alternative 
product types, and not 30-year FRMs.
    All three statistical estimations use the same conceptual 
underpinnings and empirical specifications, and only vary based on the 
data samples used in estimation. Thus, the basic definitions of the 
variables are the same across all three sets of equations, although the 
way some of the interest rate variable values change over time will 
differ, for example, for FRM loans and ARM loans, because of 
differences in their contractual terms.
    For convenience, we refer to the three separate data sets and 
statistical estimations as model 1 (30-year FRMs), model 2 (ARMs), and 
model 3 (all fixed-rate products). In addition to the basic set of 
explanatory variables included in all three models, model 3 includes 
product-specific adjustment constants. The adjustment constants act 
like multipliers to the baseline default (hazard) rates of 30-year 
FRMs. The impacts of all other explanatory variables are presumed 
constant across product type, so there are no product-type adjustments 
to their coefficients. Because ARMs are believed to perform differently 
than FRMs, due to changing payments over time, they are treated in a 
separate estimation (model 2) so that variable coefficients can be 
uniquely identified for ARM versus FRM loans.
    The explanatory variables XD(t) and Xp(t) 
used to estimate the unknown coefficients of the multinomial logit 
models are listed in Table 31. All of the variables except mortgage age 
(AGE) were coded as categorical variables. Categorical variables are 
advantageous for several reasons. For instance, assigning the various 
explanatory variable outcomes to categories allows one to estimate 
effects that may be non-linear without having to experiment with many 
different functional forms. Because each categorical explanatory 
variable has minimum and maximum categories (determined through 
observation of the historical data), the

[[Page 18177]]

impact of particular variables on rates of default or prepayment 
projected from the model is constrained to be within previous 
historical experience.\209\ This helps to avoid unreasonable 
extrapolations when projecting mortgage performance under stress test 
conditions. Another advantage of using categorical outcomes for the 
explanatory variables is that it anticipates the need to apply the 
models to aggregated loan groups in the stress test.\210\ The benefit 
of starting with loan-level data is that it allowed OFHEO to develop 
both the explanatory variables and stress test loan groups in a 
consistent manner, thus minimizing the loss of information due to data 
aggregation.
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    \209\ This constraint applies specifically to the marginal 
contribution of particular explanatory variable outcomes, not to the 
overall level of the default and prepayment probabilities projected 
by the model. For example, if several explanatory variables 
simultaneously take on values that have not been previously observed 
in combination, then it is possible that the projected probabilities 
of default or prepayment would exceed those observed in the 
historical data. This type of outcome is anticipated by the 1992 
Act, which requires regional adverse credit conditions to apply 
nationally to all loans at the same time.
    \210\ The loan groups used in the stress test were developed in 
conjunction with the classification of explanatory variable outcomes 
in the statistical analysis of mortgage default and prepayment. 
Aggregation of mortgage assets in the stress test recognizes the 
need to classify assets within broad product categories for 
financial accounting. Within the context of the proposed regulation, 
the use of aggregate loan groupings also facilitates the assignment 
of new loan products to existing categories with known risk 
characteristics. Further explanation of the aggregate loan groups 
used in the stress test is in section III. A., Mortgage Performance 
of the preamble.
---------------------------------------------------------------------------

    The summary of explanatory variables starts with descriptions of 
the two key options-related predictors of mortgage default and 
prepayment-respectively, the probability of negative borrower equity 
and the mortgage premium value. A review of additional interest rate 
variables and loan characteristics that are used as explanatory 
variables follows.
a. Probability of Negative Equity
    The put option has value to the borrower when the property is worth 
less than the outstanding balance on the mortgage. In that case, the 
borrower is in a negative equity position. Thus, the equity position of 
the borrower is determined by the difference between the market value 
of the property securing the loan, P(t), and the unpaid mortgage 
balance, UPB(t):
[GRAPHIC] [TIFF OMITTED] TP13AP99.007

    Ideally, periodic observations on the values of individual 
properties would be used to update individual house values and borrower 
equity at the same frequency (monthly) at which the decision to prepay 
or default can be exercised. However, because individual housing values 
are not updated continuously it is not possible to compute updated 
values of EQ(t) for individual borrowers with sufficient accuracy for 
this measure to be used directly at the loan level.\211\
---------------------------------------------------------------------------

    \211\ As discussed above, given the measurement difficulties 
associated with borrower equity at the loan level, some researchers 
have used various means of simulating the distribution of borrower 
equity. For example, Foster and Van Order (1984, 1985) used a Monte 
Carlo simulation of a synthetic mortgage pool in conjunction with a 
house price diffusion process and actual default and prepayment 
rates to reconstruct a time-series for the number of borrowers in a 
negative equity position. Under additional restrictions on the model 
(i.e., that only borrowers with negative equity default, and only 
borrowers with positive equity prepay), the time-series for the 
number of borrowers with negative equity (various levels) was used 
in regressions for conditional default and prepayment probabilities.
---------------------------------------------------------------------------

    It remains possible, however, to characterize the equity positions 
of individual borrowers in terms of ex ante probabilities of negative 
equity.\212\ The probability of negative equity is a function of the 
scheduled current loan balance and the likelihood of individual house 
price outcomes that lie below this value. Projected distributions of 
individual housing values relative to the value at mortgage origination 
were calculated by applying estimates of house price drift and 
volatility obtained from independent estimates based on the OFHEO House 
Price Index (HPI).\213\
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    \212\ See the discussion of ex ante probabilities of negative 
equity in footnote 199.
    \213\ House price drift is defined here as the average rate of 
house price appreciation as determined by the appropriate market 
house price index, while volatility is defined as the variance in 
individual house price appreciation rates around the market average 
rate of appreciation.
---------------------------------------------------------------------------

    The required estimates of house price drift and volatility are 
direct by-products of the estimation of the OFHEO HPI. The OFHEO HPI is 
based on a modified version of the weighted-repeat-sales (WRS) 
methodology (Case and Shiller, 1987, 1989), and is consistent with the 
assumption that housing values are generated by a log-normal diffusion 
process. This means that over time individual housing values will 
appreciate at different rates, distributed randomly around the average 
rate of appreciation. Over time, the cumulative rates of appreciation 
for individual homes will become more and more dispersed or diffused, 
hence the reference to diffusion processes. Mathematically, individual 
house prices are assumed to obey a non-stationary log-normal diffusion 
process in which individual house price appreciation since mortgage 
origination is normally distributed with variance 2 
(A) around the expected rate of appreciation from the HPI, 
(t), computed as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.008

    Where A is loan age (in quarters), and HPI(0) is the value of the 
HPI at time of loan origination.\214\ For the individual borrower with 
original house price P(0) at time 0, the probability of negative equity 
at time t, PNEQ(t) is given by:
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    \214\ Estimates of expected appreciation or drift in house 
prices are obtained directly from the estimated values of the HPI 
for each of the nine U.S. Census divisions. Estimates of diffusion 
volatility, 2(A), are computed using the 
estimated parameters for the error variance of individual log-
differences in housing prices that are obtained from the second-
stage of the WRS method for each division. See Calhoun (1996) for 
additional details. Deng, Quigley, and Van Order (1996) applied a 
similar approach using WRS indexes for 26 metropolitan areas 
estimated using Freddie Mac data.

[[Page 18178]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.009


[GRAPHIC] [TIFF OMITTED] TP13AP99.010

where (x) is the standard normal cumulative distribution 
function evaluated at x. This expression quantifies the relationship 
between changes in house prices on average, and the likelihood of 
negative appreciation on individual properties that places some 
fraction of borrowers in a negative equity position. The imputed share 
of borrowers with negative equity implied by equation 10 is used as a 
proxy for the probability of negative equity for an individual 
borrower.\215\ The computed probabilities of negative equity are 
assigned to one of eight categorical outcomes, as summarized in Table 
31.
---------------------------------------------------------------------------

    \215\ Although the market level (regional) values of house price 
drift and volatility are used, the imputed probability of negative 
equity is still specific to the individual borrower's circumstances, 
since the loan-specific values of original LTV and loan amount are 
used in the calculations.
---------------------------------------------------------------------------

b. Relative Spread
    The theoretical value of the call (prepayment) option on a mortgage 
is a function of the difference between the present value of the future 
stream of mortgage payments discounted at the current market rate of 
interest, R(t), and the present value of the mortgage evaluated at the 
current note rate, C(t). The actual value of this call option to the 
borrower is unknown due to uncertainty over the future time path of 
mortgage payments associated with uncertain future probabilities of 
prepayment and default. Therefore, it is common to use other variables 
to capture the impact of the call option value on prepayment rates. 
Following recent work by Deng, Quigley and Van Order (1996), OFHEO 
approximated the call option value using the relative spread variable, 
RS(t):
[GRAPHIC] [TIFF OMITTED] TP13AP99.011

    Positive values of the call option exist when the mortgage coupon 
exceeds the current market interest rate (positive spread), and the 
borrower can benefit financially by refinancing to obtain a lower 
interest rate. Outcomes for the relative spread variable are classified 
into seven categorical outcomes, as summarized in Table 31.
c. Prepayment Burnout
    Recent studies of mortgage terminations have emphasized the 
importance of previous interest rate environments for distinguishing 
among borrowers more or less likely to exercise the prepayment option 
when the opportunity arises.\216\ The tendency for the most responsive 
borrowers to prepay first, so that the remaining sample of borrowers 
are those with lower average conditional probabilities of prepayment, 
contributes to the observed seasoning or ``burnout'' of mortgage pools. 
The indicator variable B(t) is included to measure whether the borrower 
has missed a previous refinance opportunity.\217\ B(t) is defined by 
whether the market rate of interest was 200 basis points or more below 
the coupon rate of the mortgage during two or more quarters over the 
past two years. Those who have missed previous refinance opportunities 
are predicted to have lower conditional probabilities of prepayment and 
higher conditional probabilities of default. Failing to refinance under 
favorable interest rate conditions may indicate the existence of other 
credit-related problems, such as failure to obtain an adequate property 
appraisal.\218\
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    \216\ For example, see the discussions of borrower heterogeneity 
and path dependence in Bartholomew, Berk, and Roll (1988), and the 
discussion of burnout in Richard and Roll (1989).
    \217\ The indicator variable equals one if the spread between 
the note rate on the mortgage and the quarterly average market rate 
of interest has been 200 basis points or greater during any two of 
the past eight quarters.
    \218\ See footnote 198.
---------------------------------------------------------------------------

d. Yield Curve Slope
    Expectations about future interest rates and differences in short-
term and long-term borrowing rates associated with the slope of the 
Treasury yield curve influence the choice between ARM and FRM loans and 
the timing of refinancings and prepayments. A high value for the slope 
of the yield curve indicates relatively favorable short-term rates, 
increasing the likelihood that a borrower refinances to an ARM to take 
advantage of the lower initial coupons that can be offered by lenders. 
The variable YS(t) is included to measure the current slope of the 
yield curve. This variable is computed as the ratio of the ten-year 
Constant Maturity Treasury yield (CMT) to the one-year CMT, and 
assigned to four categorical outcomes.
e. Mortgage Age
    The existence of other demographic and economic processes that may 
``trigger'' mortgage default or prepayment, and the inability to 
measure the diffusion of house prices and the distribution of borrower 
equity precisely, create a need to account directly for age-specific 
differences in conditional rates of default and prepayment.\219\ The 
direct dependence of the conditional probabilities on mortgage age 
recognizes the existence of other borrower processes and unobserved 
heterogeneity that induce duration dependence in the conditional rates 
of termination and help to explain the typical age patterns of default 
and prepayment.\220\ For this reason,

[[Page 18179]]

mortgage age (AGE) is included as an additional explanatory variable in 
the empirical model. The model utilizes a quadratic function of 
mortgage age, where age is defined as the number of quarters since 
origination. The use of a parametric function of age instead of 
categorical values is based on two considerations. First, the use of 
categorical age values for individual quarters would result in a large 
number of additional coefficients to estimate. Combining loans into 
broader age groupings to reduce the number of parameters can produce 
large differences in rates of default and prepayment with small 
increments in age for loans graduating from one age category to the 
next. Second, when individual age categories are used, they show that a 
quadratic age function is a reasonable assumption, at least for the 
first eight to ten years. At higher values of mortgage age, the samples 
are much smaller (most loans have terminated by these ages), with the 
result that the estimates for individual age categories are quite 
erratic due to sampling error. The use of a simple functional form like 
the quadratic helps to smooth the estimates of the age effects for the 
higher age groups.
---------------------------------------------------------------------------

    \219\ Under a pure options model, the typical age patterns of 
conditional default and prepayment rates might be attributed 
entirely to the diffusion of housing values and the introduction of 
unobserved differences (heterogeneity) in the equity positions of 
individual borrowers, resulting in differences in the rates of 
default and prepayment among particular subsets of individual 
borrowers. As these differences emerge following mortgage 
origination, the observed average conditional default and prepayment 
rates will initially increase. Eventually, as ``high risk'' 
borrowers depart the sample or mortgage pool, the average 
conditional rates of default and prepayment will decline.
    \220\ See Lancaster (1990) for a discussion of the impact of 
unobserved heterogeneity on estimates of duration dependence in 
econometric models of transition probabilities. Other borrower 
processes include residential mobility, employment mobility, 
involuntary unemployment, and demographic events related to 
household formation and dissolution, mortality, and fertility. 
Ideally, given suitable household-level data, these other processes 
would be modeled jointly with mortgage terminations.
---------------------------------------------------------------------------

f. Original LTV
    The original LTV ratio, LTV(0), serves as an indicator of the 
income and net worth of the borrower at mortgage origination, and 
directly determines the initial equity position of the borrower. To the 
extent that income and wealth are negatively correlated with LTV(0), 
high LTV borrowers will have fewer economic resources to finance the 
transactions costs of prepayment or endure spells of unemployment or 
other trigger events that might otherwise cause them to exercise the 
default option in a sub-optimal manner. Finally, high LTV borrowers 
have already demonstrated a willingness to ``leverage'' the financing 
of the home purchase, which may portend a greater sophistication or 
``ruthlessness'' in the exercise of the default option. Thus, one would 
expect higher rates of default and lower rates of prepayment as LTV(0) 
increases. The six LTV(0) categories used in the default/prepayment 
models are similar to those used by the Enterprises in their annual 
reports and information statements.
g. Season of the Year
    The variable SEASON(t) was included to account for the current 
season (quarter) of the calendar year, in recognition of the potential 
impact of weather, school schedules, and seasonal employment patterns 
on residential mobility and default and prepayment probabilities.
h. Occupancy Status
    OS is an indicator variable included to distinguish mortgages on 
owner-occupied units from investor loans. Owner occupants should be 
less likely than investors to exercise the default option given the 
direct benefits they receive from the consumption of housing services. 
Owner occupants should be more likely to prepay than investors for non-
financial reasons such as residential mobility.
i. Relative Loan Size
    The ability to bear the transactions costs of refinancing, or to 
weather economic stress and avoid default, will be correlated with the 
income level of the household. Given the lack of information in the 
historical data on household income at origination, a measure of 
relative loan size provided a proxy for the relative income level of 
the household. LOANSIZE was defined as the ratio of the original loan 
amount relative to the average-sized Enterprise loan originated in the 
same State during the same origination year.\221\
---------------------------------------------------------------------------

    \221\ Price Waterhouse (1990) reported significant differences 
in claim rates for FHA mortgages stratified by loan size. Smaller 
loans were observed to fail at significantly higher rates than other 
loans.
---------------------------------------------------------------------------

j. Product Type Indicators
    Five product type indicators were created to account for the 
performance of non-standard loans relative to the standard 30-year FRM 
loans in model 3: 20-Year FRM, 15-Year FRM, balloon, FHA/VA, and 
seconds. These indicator variables provide the adjustment constants 
mentioned earlier.
k. ARM Coupon Rate Dynamics
    To estimate the current values of both the probability of negative 
equity, PNEQ(t), and the relative spread, RS(t), variables for ARM 
loans, it was necessary to trace the path of current coupon rates over 
the active life of individual mortgages. For standard ARM products, the 
coupon rate resets periodically to a new level that depends on the 
underlying index, plus a fixed margin, subject to periodic and lifetime 
interest rate caps that specify the maximum and minimum amounts by 
which the coupon can change on any one adjustment and over the life of 
the loan.\222\ ARM coupon rates are updated using the following 
formula:
---------------------------------------------------------------------------

    \222\ Detail on specific ARM contracts was obtained in some 
cases from loan-level information, and in other cases was obtained 
using plan-level detail for loans in certain ARM product categories. 
Any loan product with variable interest rates was classified as an 
ARM, and modeled according to product terms. This includes so-called 
two-step mortgages and mortgages with interest-rate buydowns. For 
simplicity, the margin was set at 2 percent for all ARMS.
[GRAPHIC] [TIFF OMITTED] TP13AP99.012

    Where Index (t) is the underlying index value at time t, S is the 
``lookback'' period, and Margin is the amount added to Index (t--S) to 
obtain the ``fully-indexed'' coupon rate. The periodic adjustment caps 
are given by PeriodUpCap and PeriodDownCap, and are multiplied by an 
indicator variable A(t) which equals zero except during scheduled 
adjustment periods. The maximum lifetime adjustments are determined by 
and LifeUpCap and LifeDownCap.\223\
---------------------------------------------------------------------------

    \223\ The majority of Enterprise ARM loans are indexed to the 
one-year Treasury rate, with smaller but significant numbers indexed 
to either the five-year or ten-year Treasury rate, the 11-District 
Cost of Funds Index (COFI), or the London Inter-Bank Offer Rate 
(LIBOR). A small percentage of ARM loans are indexed to the six-
month or three-year Treasury rates. The majority of ARM loans had 
lifetime adjustment caps of five or six percent, and have no 
lifetime rate floors. Most have periodic rate adjustment caps of two 
percent, while some have periodic rate adjustment caps of one 
percent. The majority of ARM loans have adjustment frequencies of 
one year, while a significant minority are adjusted every six 
months.

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[[Page 18180]]

6. Empirical Results
    The three models were estimated by the method of maximum likelihood 
using the SAS CATMOD procedure. The CATMOD procedure 
employs a design matrix that automatically converts all categorical 
variables to a series of indicator variables prior to estimation. As 
discussed above, all explanatory variables except mortgage age were 
converted to indicator variables. This allows one to reduce the data to 
a smaller number of loan records, each representing unique combinations 
of the categorical variables, to which a frequency count is assigned 
and applied as a sampling weight in subsequent statistical analyses. 
This approach avoids the need to undertake choice-based sampling (e.g., 
over-sampling of defaulted loans) in order to assure that sufficient 
numbers of rare events like mortgage default are obtained.\224\ 
However, given the large number of loan level observations available to 
OFHEO, simple random samples were used to estimate the 30-Year FRM and 
Multiple Products models. All available data were used to estimate the 
ARM model.\225\
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    \224\ It has been demonstrated for static logit models that 
choice-based sampling results in biased estimates of the 
coefficients of the logit constant terms, for which relatively 
simple corrections are available, based on the population 
distribution of the explanatory variables across groups defined by 
dependent variable outcomes (Costlett, 1981). It is not clear that 
the same form of correction applies to the retrospective event-
history sample used in this analysis. Selection on the basis of 
default outcomes implies selection of an array of preceding ``non-
events'' for each quarter the loan was active, so that the 
distributions of the explanatory variables for specific age 
categories depends on the timing of default events for individual 
loans.
    \225\ A ten-percent random sample was used for the 30-Year FRM 
model and the Multiple Products model. All data used for estimation 
were subject to a variety of data quality screens and available data 
for all the explanatory variables.
---------------------------------------------------------------------------

    Table 32 contains the parameter estimates for the three 
models.\226\ The constant and age parameters are listed first, as they 
provide a baseline function to which the effects of other variables can 
be added. There is a high level of consistency in the coefficient 
estimates across all three models, and all three models provide 
empirical support for the importance of the options-related variables.
---------------------------------------------------------------------------

    \226\ Note that a particular feature of the SAS CATMOD procedure 
is that when it estimates the coefficients corresponding to a 
variable with N categories, the program estimates only the first N-1 
coefficients. The final-category coefficient for each variable is 
computed as the additive inverse of the first N-1 category 
coefficients.
---------------------------------------------------------------------------

    The coefficient estimates for the probability of negative equity 
variable (PNEQ) vary on the same order of magnitude for default as the 
coefficient estimates for the original LTV variable. PNEQ is also 
important for prepayment, in the opposite direction, consistent with 
the expectation that those most likely to have negative equity will 
have the greatest difficulty selling their homes or refinancing their 
mortgages, and therefore be less likely to prepay their existing 
mortgages. Original LTV is relatively unimportant for prepayment, 
although those in the lowest LTV category are more likely to prepay.
    The value of the call option measured by the relative spread (RS) 
shows quite large effects on prepayment in the hypothesized direction. 
The higher the coupon rate on the mortgage relative to the current 
market rate of interest the higher the likelihood of prepayment. Note 
the general similarities between the RS coefficient estimates for 
models one and two (30-year FRMs and ARMs). Because ARM coupon rates 
will adjust with changes in market rates, ARM borrowers are less likely 
than FRM borrowers to end up with large positive or negative RS values. 
However, the estimates in Table 32 imply that ARM and FRM borrowers 
behave in a similar manner under comparable values of the call option.
    The prepayment burnout variable, B, is most important for default 
rates, and indicates that missed opportunities to prepay are associated 
with higher credit risk. This result reinforces the results discussed 
above for PNEQ, where higher values of PNEQ were associated with lower 
probabilities of prepayment. This result also reflects the lack of 
precision in measurements of borrower equity at the loan level.
    The slope of the yield curve (YS) is important for the probability 
of prepayment for FRM borrowers, especially for steep positive values 
of the slope. This result is consistent with the tendency of borrowers 
to refinance to ARM mortgages when short-term rates are relatively low 
and lenders can offer very favorable initial coupons (``teaser'' 
rates). It is also consistent with the assumption that the expectation 
of higher interest rates in the future may cause some borrowers to 
refinance sooner to lock in lower rates. The yield curve slope variable 
has similar, but smaller, effects for ARM borrowers.
    The SEASON variable has modest effects in the anticipated 
directions. For FRM borrowers, prepayment rates are lower than average 
in the Winter and higher in the Spring. Default rates are lower in the 
Winter and higher in the Fall. For ARMs, prepayments are also higher in 
the Fall, but defaults are lower in that season.
    Occupancy status (OS) has much larger impacts on default 
probabilities for ARM borrowers than FRM borrowers. For both product 
types, investors are more likely to default than owner-occupants, and 
much more so for ARM borrowers than FRM borrowers. It is reasonable to 
expect that owner-occupants will be less ruthless in the exercise of 
the default option given the offsetting value they receive from living 
in the home. The prepayment effects are more similar across ARM and FRM 
borrowers.
    The variable LOANSIZE was included as a proxy for borrower income 
at origination. The results in Table 32 indicate that relative loan 
size is not particularly important for default probabilities, at least 
after controlling for the other explanatory variables. LOANSIZE is much 
more important for prepayment, with smaller loans prepaying at lower 
rates than relatively large loans. This is consistent with the 
interpretation of LOANSIZE as a proxy for borrower income. Lower income 
borrowers may lack the resources to bear the transactions costs of 
refinancing, causing them to prepay at lower rates than higher income 
borrowers with relatively large loans. Lower income borrowers may also 
be less mobile than higher income borrowers. The results for prepayment 
are similar across FRM and ARM borrowers.
    The results for the two fixed-rate models, models one and three, 
are generally quite consistent. The individual product type indicators 
in model 3 provide estimates of the relative rates of default and 
prepayment of various fixed-rate products in comparison to 30-Year 
FRMs, and in comparison to each other. Balloon mortgages have the 
highest rates of default and prepayment relative to 30-Year FRMs. 
Intermediate FRM products (15-Year and 20-Year) default at lower rates 
than 30-Year FRMs. This result is consistent with more rapid loan 
payoff and accumulation of borrower equity for these borrowers. Rates 
of prepayment on intermediate FRMs are comparable to those on 30-Year 
FRMs. FHA and VA loans have higher rates of default and lower rates of 
prepayment than 30-Year FRM loans. Results for the category of second 
loans is most similar to the FHA/VA loans.
7. Application of the Models in the Stress Test
    The three product-based single family models provide the means to 
project the conditional default and prepayment probabilities required 
as inputs to the cash flow model of Enterprise financial

[[Page 18181]]

performance. The stress test aggregates single family loan-level data 
into loan groups based on the following characteristics: Enterprise, 
portfolio (securitized vs. retained), product type, origination year, 
original LTV ratio class, original coupon class, starting coupon class, 
and region (Census division). The information contained in 
characteristics data for each aggregated loan grouping is sufficient, 
when combined with data on house price growth rates and interest rates, 
to compute and update all of the explanatory variables needed for 
computing conditional default and prepayment probabilities during the 
stress period.
    There are three exceptions to this general statement. The variables 
SEASON and LOANSIZE were not used to classify loans for the purpose of 
the stress test. The SEASON variable was excluded when applying the 
logit models to project default and prepayment probabilities over the 
stress period.\227\ The LOANSIZE variable was retained, but all loans 
were categorized as being of average size. These two changes reduced by 
a factor of nine the number of loan groups that had to be processed 
when running the stress test. Accounting for seasonal effects and 
differences in default and prepayment rates by loan size was not 
considered essential for projecting mortgage performance in the stress 
test.\228\ In addition, the variable OCCUPANCY, used to distinguish 
mortgages on owner-occupied units from investor loans, is replaced by 
the portfolio average percentages for each occupancy status. Thus, 
instead of creating separate loan groups for owner-occupied and 
investor loans, these loans are combined into a single group, and a 
weighted average of the logit coefficients for owners and investors is 
used when projecting default and prepayment probabilities. This 
procedure reduces the number of records that must be processed by a 
factor of 2, but still allows OFHEO to account for changes over time in 
the percentage of Enterprise mortgages that are investor loans.
---------------------------------------------------------------------------

    \227\ The parameter estimates generated by the SAS CATMOD 
procedure are defined so that they sum to zero across all categories 
of a given explanatory variable. This implies that dropping them 
from the model is equivalent to assuming that the logit 
probabilities for default and prepayment include the average effect 
across all the possible categories of the excluded variable.
    \228\ Including the SEASON variable in estimation can be 
justified because it helps to isolate the statistical impact of 
changes in house prices on borrower equity from purely seasonal 
fluctuations in default and prepayment rates. Likewise, LOANSIZE and 
original LTV are both likely to be related to borrower income and 
wealth at mortgage origination. However, because LOANSIZE is defined 
relative to the average sized loan within a state in the year of 
origination it provides a somewhat different measure of relative 
income or wealth.
---------------------------------------------------------------------------

    The detail contained in the starting position loan group records is 
sufficient to treat each loan group as if it performs like a single 
loan, with the projected probability of default or prepayment from the 
model corresponding to the share of the loan group balance that will 
default or prepay in any given period (i.e., by the ``law-of-large-
numbers''). Group-specific average values of original LTV and mortgage 
coupon are used in place of exact loan-specific values in computing 
explanatory variables requiring these as inputs (e.g., PNEQ and RS). 
Categorical values such as original LTV and region (Census division) 
are classified in the same way for both the loan-level data used for 
estimation and the loan groupings used in the stress test.
    Another nuance of stress test implementation is that, for purposes 
of projecting default and prepayment rates, OFHEO treats all mortgages 
with variable payments as if they were standard one-year Treasury ARMs, 
with identical payment caps and interest rate margins. In contrast, in 
the statistical analysis, specific payment changes for each loan type 
were reflected in the creation of explanatory variables.
    In the development of explanatory variables for both the 
statistical analysis and stress test implementation, a shortcut is used 
to amortize ARMs. At each payment adjustment date, the new mortgage 
payments are computed using updated interest rates but with the 
original UPB and loan term, rather than current UPB and remaining term. 
This is seen in the formula used for PMTq, which is the same 
for both fixed- and adjustable-rate mortgages. (See section 3.5.2.3, 
Procedures of the Appendix.) This approach provides an approximation 
for actual payment changes on adjustable rate mortgages. It expedites 
calculations by reducing the code necessary to update payments and UPB 
in each quarter. The approximation here should have little effect on 
default rate results because of the use of categorical, rather than 
continuous explanatory variables. Differences in loan amortization 
arising from using this payment-calculation approximation only affect 
default or prepayment rates when those differences move the probability 
of negative equity variable from one (value) category to another. Loan 
amortization in the Cash Flow component of the stress test does not use 
this shortcut.
    In the development of variables for both the statistical analysis 
and stress test implementation, the incorrect term is used to amortize 
balloon loans. Mortgage origination term (T0), rather than 
mortgage amortization term (Ta), is used to amortize these 
loans. This is seen in the formula used for PMTq, which does 
not distinguish between balloon loans and other loan products. See 
section 3.5.2.3, Procedures of the Appendix. Amortization of balloon 
loan products in the Cash Flow component of the stress test uses the 
mortgage amortization term.
8. Consistency With the Historical Benchmark Experience
    Certain adjustments and assumptions to the models were made to 
assure consistency of the rates of default projected in the stress test 
with the BLE. Loan-level data from the benchmark was aggregated in the 
same way current Enterprise loan groups are formed in the stress test, 
and the 30-year FRM model was applied to these data to project 
conditional and cumulative default and prepayment rates for the ten 
years following origination.\229\ A single set of house price 
appreciation rates from the OFHEO HPI, the ten-year sequence of 
appreciation rates from the West South Central Census division for the 
period from 1984 Q1 to 1993 Q4, was applied to every benchmark loan 
group.\230\ Actual historical interest rates were used. The projected 
average ten-year cumulative default rate was compared to that observed 
for the BLE, and adjustments were made to the constant term 
D of the default function until the projected and 
observed default rates were equal.\231\
---------------------------------------------------------------------------

    \229\ Note that all loans of the BLE are newly originated loans.
    \230\ The West South Central Census Division does not exactly 
match the 4-State benchmark region, but its use here to represent 
benchmark economics is consistent with OFHEO's proposal to aggregate 
data based on Census divisions, and to apply historical Census 
division-level house price growth rates to season loans at the 
beginning of the stress test. What is most important is that the 
price series used to calibrate the statistical equations is the same 
series that will be used in the stress test itself. The actual ten-
year house-price experience of the West South Central Division and 
the 4-State benchmark area, 1984-1993, are very similar.
    \231\ When computing the cumulative default rate projected by 
the model for comparison with that observed for the benchmark 
experience, the same calculations were used. The model was used to 
project the total defaulting UPB for benchmark loans over the ten-
year period following origination for each monthly origination 
cohort. The total defaulting UPB for each Enterprise was obtained by 
summing up the total defaulting UPB for each origination cohort, 
which was divided by the total original UPB for that Enterprise to 
compute the ten-year cumulative default rate. The two Enterprise 
cumulative default rates were then averaged. As discussed in NPR1, 
because of missing data on defaulting loans, OFHEO used the original 
UPBs on default loans in place of UPB at the time of default. This 
has little effect on the resulting historical loss rates, because 
the same values for defaulting UPBs were used when computing 
severity rates. In the calibration of default rates, the UPBs at the 
time of default projected from the model (which take into account 
normal amortization) were adjusted back to their origination values 
for consistency with the benchmark methodology.

---------------------------------------------------------------------------

[[Page 18182]]

    The adjusted (calibrated) model is then applied in the stress test, 
along with the sequence of house price appreciation rates used in the 
calibration procedure.\232\ Therefore, if newly originated loans with 
characteristics similar to those comprising the benchmark sample were 
subjected to the same economic circumstances as occurred in the 
benchmark experience, then the statistical model of mortgage 
performance would project ten-year cumulative default rates equal to 
those of the benchmark sample. Conversely, to the extent interest 
rates, property values, and loan characteristics are different from the 
benchmark sample, and to the extent adjustments are necessary to 
account for other statutory requirements (e.g., increased general 
inflation under large increases in the ten-year CMT), the stress test 
rates differ from the benchmark level.
---------------------------------------------------------------------------

    \232\ In the calibration, all loans of the BLE are assigned an 
HPI volatility parameter estimate based on the West South Central 
Census division. In the stress test, loans from each region retain 
their respective regional volatility values.
---------------------------------------------------------------------------

    The adjustment of the model is appropriate for use in the stress 
test because the statistical equations in the model were estimated 
using Enterprise data on loans from a broad range of times and places, 
in addition to those loans included in the benchmark sample. Because, 
by definition, the BLE reflects the highest rates of loss observed from 
among these other periods and places, the model would not be likely to 
replicate benchmark results on benchmark loans exactly without some 
type of adjustment.
    The calibration procedure does not add an adjustment factor to 
match projected prepayment rates directly to the benchmark prepayment 
experience. Nevertheless, the stress test model is fully calibrated to 
the credit loss experience of the benchmark loans because the 
calibrated default equation, and the uncalibrated prepayment equation 
that was used to help calibrate the default equation, are used together 
to determine mortgage performance. Because the time paths of Treasury 
yields and mortgage rates used in the calibration were those 
corresponding to the individual benchmark origination cohorts, the 
conditions leading to prepayments in the calibration exercise are 
entirely consistent with the benchmark default experience.

[[Page 18183]]

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[[Page 18184]]

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[[Page 18185]]

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[[Page 18186]]

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[[Page 18187]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.220


9. References
Bartholomew, L., J. Berk, and R. Roll (1988). ``Adjustable Rate 
Mortgages: Prepayment Behavior,'' Housing Finance Review, 7:31-46.
Brennan, M. J., and E. S. Schwartz (1985). ``Determinants Of GNMA 
Mortgage Prices,'' AREUEA Journal, 13:209-228.
Buser, S. A., and P. H. Hendershott (1984). ``Pricing Default Free

[[Page 18188]]

Mortgages,'' Housing Finance Review, 3:405-429.
Calhoun, C.A. (1996). ``OFHEO House Price Indexes: Technical 
Description,'' Washington, D.C., Office of Federal Housing Enterprise 
Oversight, April 1996.
Campbell, T.S. and J.K. Dietrich (1983). ``The Determinants of Default 
on Insured Conventional Residential Mortgage Loans,'' Journal of 
Finance, 38:1569-1581.
Case, K.E. and Shiller, R.J. (1987). ``Prices of Single Family Real 
Estate Prices,'' New England Economic Review. 45-56.
Case, K.E. and Shiller, R.J. (1989). ``The Efficiency of the Market for 
Single-Family Homes,'' The American Economic Review, 79, 125-137.
Costlett, S. (1981). ``Efficient Estimation of Discrete-Choice 
Models,'' pp. 51-111 in C.F. Manski and D. McFadden (eds.), Structural 
Analysis of Discrete Data with Econometric Applications, Cambridge, 
Massachusetts: MIT Press, 1981.
Cunningham, D., and C. Capone (1990). ``The Relative Termination 
Experience Of Adjustable To Fixed-Rate Mortgages,'' The Journal of 
Finance, 45(5):1687-1703.
Deng, Y. (1997). ``Mortgage Termination: An Empirical Hazard Model With 
Stochastic Term Structure,'' The Journal of Real Estate Finance and 
Economics, 14(3), forthcoming.
Deng, Y., J.M. Quigley and R. Van Order (1996). ``Mortgage Default And 
Low Downpayment Loans: The Costs Of Public Subsidy,'' Journal of 
Regional Science and Urban Economics, 26(3-4):263-285.
Dunn, K.B. And J.J. McConnell (1981). ``Valuation Of Mortgage-Backed 
Securities,'' The Journal of Finance, 36:599-617.
Foster, C., and R. Van Order (1984). ``An Option-Based Model of 
Mortgage Default,'' Housing Finance Review, 3(4):351-372.
Foster, C. and R. Van Order (1985). ``FHA Terminations: A Prelude to 
Rational Mortgage Pricing,'' AREUEA Journal, 13(3):273-291.
Hendershott, P. H. And R. Van Order (1987). ``Pricing Mortgages: An 
Interpretation Of The Models And Results,'' Journal of Financial 
Services Research, 1:77-111.
Kau, J.B., D.C. Keenan, W. J. Muller, and J. F. Epperson (1985). 
``Rational Pricing Of Adjustable Rate Mortgages,'' AREUEA Journal, 
13(2):117-128.
Kau, J.B., D.C. Keenan, W. J. Muller, and J. F. Epperson (1990). ``The 
Valuation And Analysis Of Adjustable Rate Mortgages,'' Management 
Science, 36(12):1417-1431.
Lancaster, T., The Econometric Analysis of Transition Data, New York: 
Cambridge University Press, 1990.
Manski, C.F. and D. McFadden (1981), ``Alternative Estimators and 
Sample Designs for Discrete Choice Analysis,'' pp. 2-50 in C.F. Manski 
and D. McFadden (eds.), Structural Analysis of Discrete Data with 
Econometric Applications, MIT Press, 1981.
McFadden, D. (1976), ``Quantal Choice Analysis: A Survey,'' Annals of 
Economic and Social Measurement, 5:363-390, 1976.
Price Waterhouse. An Actuarial Review of the Federal Housing 
Administration's Mutual Mortgage Insurance Fund, Washington, DC: Price 
Waterhouse, 1990.
Richard, S.F. and R. Roll (1989). ``Prepayments on Fixed Rate Mortgage 
Backed Securities,'' Journal of Portfolio Management, 15(3):73-82.
Schwartz, E.S. And W.N. Torous (1989). ``Prepayment And The Valuation 
Of Mortgage-Backed Securities,'' The Journal of Finance, 44(2):375-392.
Vandell, K.D. ``Handing Over the Keys: A Perspective on Mortgage 
Default Research,'' AREUEA Journal, 21(3):211-246.
Zorn, P., and M. Lea (1986). ``Adjustable Rate Mortgage, Fluctuations 
In The Economic Environment And Lender Portfolio Change,'' AREUEA 
Journal, 14:432-447.

C. Single Family Loss Severity

1. Introduction
    This supplementary material provides information on the estimation 
and application of statistical models for the single family loss 
severity component of the proposed risk-based capital stress test and 
regulation. With one exception, all cost and revenue elements of loss 
severity are calculated as averages of historical Enterprise experience 
with foreclosed mortgages. The one exception is that a statistical 
regression model was developed to project the sale proceeds on 
foreclosed (real estate owned, or REO) properties. This regression 
model uses the same property valuation process that was used to create 
a probability of negative equity variable in the default/prepayment 
analysis. However, in projecting REO sales proceeds, the process is 
used to create a variable that measures the average equity of 
performing loans that have the same characteristics (other than equity) 
as defaulting loans. The regression then describes the relationship 
between average equity of performing loans and average (negative) 
equity of defaulting loans. One minus the projected negative equity on 
defaulting loans gives the projected REO sale proceeds. This regression 
analysis allows stress test loss severity rates to reflect economic 
conditions and provides an opportunity to reasonably relate loss 
severities on current Enterprise portfolios to the benchmark 
experience.
    With the exception of government insured loans, OFHEO's loss 
severity analysis does not make explicit distinctions by loan product 
type. Differences by loan products are captured in the basic loan 
terms--coupon rate, LTV, and amortization term-that factor into loss 
severity equations.
    The Enterprises rely upon various counterparties to provide credit 
enhancements that offset gross severity rates. An explanation of how 
credit enhancements are modeled in the stress test can be found in the 
appendix to the regulation.
    The remainder of this supplementary material is organized as 
follows: section 2 provides the conceptual framework for single family 
loss severity analysis; section 3 describes the data used in the 
analysis; section 4 discusses the statistical analysis; section 5 
examines adjustments made to the severity equations to reasonably 
relate the results to the historical benchmark experience identified in 
the first NPR; and section 6 explains how the results of the 
statistical analysis are applied in the stress test.
2. Conceptual Framework
    In determining the approach to use in modeling loss severity rates, 
OFHEO reviewed four research studies. None of these attempted to 
analyze the various components of loss severity, but rather used simple 
regressions of some measure of a gross severity rate on original loan-
to-value and loan age. These studies provide little guidance, as they 
do not provide frequency distributions of observed severity rates, nor 
do they provide averages y loan types.\233\
---------------------------------------------------------------------------

    \233\ These studies are: Clauretie (1990), Lekkas, Quigley, and 
Van Order (1993), Crawford and Rosenblatt (1995), and Berkovec, et 
al. (1997). The Berkovec, et al. study is not focused on loss 
severities, but rather analyzes them as part of a broader study of 
potential lending discrimination. These four studies are reviewed by 
Capone and Deng (1998), who themselves are interested in variations 
in loss severity rates across defaulted loans that can be explained 
by the tenets of option pricing theory. See also Kau and Keenan 
(1997) for the one example of severity analysis in a theoretical 
mortgage pricing model.
---------------------------------------------------------------------------

    OFHEO chose to analyze defaulted loan severity rates in three 
parts: loss of loan principal, transaction costs, and

[[Page 18189]]

funding cost. This decomposition was used for three reasons. First, the 
loss of unpaid principal loan balance (UPB) is a function of the loss 
of property value before and during the default period, which can be 
statistically modeled as a function of economic conditions. The second 
reason for a decomposition analysis is to accommodate the timing of 
various cash flows during the period between initial default (month of 
first missed payment) and final property disposition. In the stress 
test, all default losses are accounted for in the month of default. The 
loss severity rate accounts for the timing of income and expenses after 
the default month. The timing of post-default cash flows is captured 
using present value discounting techniques. This method also captures 
funding costs of the nonearning assets-first the mortgage, and then the 
REO. Finally, the stress test calibrates the severity component related 
to loss of principal balance to the economic conditions of the BLE, as 
will be discussed in section 5. The stress test also uses BLE data for 
the elapsed time between default and foreclosure completion, and 
between foreclosure completion and property disposition.
    Loss severity is most frequently expressed as a rate rather than a 
dollar amount. The most accurate representation of the magnitude of 
losses is to express loss severity as a percentage of the UPB at the 
time of default. Therefore, OFHEO has chosen to calculate all costs and 
revenues associated with loss severity as a percentage of the UPB. This 
will result in the computation of loss severity rates rather than 
dollar amounts, but they become dollar amounts when the stress test 
multiplies both default and loss severity rates against loan balances.
3. Data
    Loan level data on Enterprise single family REO properties were 
used to analyze the components of single family loss severity rates. 
The data contain all defaulted mortgages on single family (1-4 unit) 
properties that were both originated and had a last-paid-installment 
date between January 1980 and December 1995. After removing incomplete 
records, over 116,500 valid records remained in the analysis database. 
These records consist of loan terms, event dates (default, foreclosure, 
disposition), and various expense and revenue fields.
    A second analysis database was created consisting of only those 
loans in the historical REO analysis database that met benchmark 
criteria. Those criteria singled out conventional, 30-year fixed-rate 
loans on single family properties (single unit, owner-occupied, 
detached properties) that originated in 1983 and 1984 in the States of 
Arkansas, Louisiana, Mississippi, and Oklahoma, and defaulted within 
ten years of origination. This benchmark database (789 loans) was used 
to create an adjustment factor that provides consistency between the 
loss severity rates projected in the stress test and the benchmark loss 
rates. This process is discussed in section 5, Consistency with the 
Benchmark Loss Experience, below.
    Other data used in the analysis of loss severity rates includes 
historical Census division level HPI indices and their associated 
volatility parameters, which come from the OFHEO HPI Report, 1996:3.
4. Statistical Analysis
    The primary statistical analysis performed for single family loss 
severity rates measured the impact of market conditions on REO sale 
proceeds. This is the one dynamic element of loss severity in stress 
test application. It relies upon original LTV, loan amortization, and 
Census division level house price growth. OFHEO performed a statistical 
regression analysis to model negative equity for defaulted loans as a 
function of the average equity of similar, but performing, loans. All 
other statistical analyses involved calculating average historical 
experience by loss severity element. The two elements with values 
computed as historical averages are foreclosure expenses and a 
combination of REO expenses, revenues (other than disposition 
proceeds), and property selling expenses. In addition, average times to 
foreclosure and time in REO were computed for use in calculating the 
net present value of revenues and expenses in the month of default.
    When averages were computed for loss elements, a two-step procedure 
was used. First, the average experience of each firm was calculated 
using UPB as a weighting factor. This weighted average provides a good 
measure of portfolio-wide performance, although the analysis is based 
on individual loans. The second step was to give equal weight to the 
experience of each firm by taking a simple average of the experience of 
the two Enterprises. This procedure is also consistent with the 
procedure used to find the benchmark loss severity rate reported in 
NPR1.\234\
---------------------------------------------------------------------------

    \234\ See 61 FR 29592, 29597, June 11, 1996. Procedures here 
differ from those of the first NPR by calculating loss severity as a 
percentage of the outstanding loan balance at time of default, 
rather than a percentage of the original loan balance.
---------------------------------------------------------------------------

    The averages of the foreclosure and the REO expense/revenue 
elements are based on the entire national, historical sample of 
Enterprise experience. Benchmark experience was not used by itself 
because it was evident from an analysis of the data that there were 
significant numbers of records with missing expense components. The 
magnitudes of these expense items should not vary between the benchmark 
region and other areas of the country for two reasons. First, the 
benchmark region has a variety of foreclosure laws, by State, so that 
the average foreclosure expense rate for the benchmark region is 
similar to averages from other regions of the country, and to the 
average for the nation as a whole. Second, OFHEO computed these loss 
components as percentages of the outstanding loan balance, rather than 
as actual dollar amounts. Thus, the fact that the benchmark region may 
have had lower property values than the national average, and therefore 
lower dollar losses per loan, will not be material. Average loss rate 
components from other regions of the country should be comparable to 
what would be found in the benchmark loan data, if those records were 
complete.
    OFHEO does, however, base time frames on benchmark experience. 
Because the benchmark region does have a variety of foreclosure laws, 
these time frames are actually very close to those of the entire 
national experience of the Enterprises.

a. Predicting REO Sale Proceeds

    The REO sale proceeds, as a percentage of the defaulting UPB, 
measures the impact of erosion of property value over time, both prior 
to and after default. To begin the analysis of REO sale proceeds, OFHEO 
computed negative property equity, the difference between the 
defaulting UPB and the gross property sale proceeds, as a percentage of 
the UPB.\235\ This amount was regressed against average equity for 
similar, but non-defaulting loans. The resulting regression coefficient 
provides the relationship between average equity of performing loans 
and average (negative) equity of defaulting loans. The nuance here is 
that average equity of performing loans is first transformed into a 
standardized normal distance, or what is commonly called a z-score, 
before being used in the regression. This is a widely used statistical 
technique for

[[Page 18190]]

creating a standard unit of measure for comparisons across many 
different variables and/or value levels.
---------------------------------------------------------------------------

    \235\ The one expense that OFHEO does net from sale proceeds 
here is property repairs undertaken by the Enterprises during the 
REO period. Because these expenses reflect part of the loss of 
property value that occurred prior to foreclosure completion, it is 
appropriate that they be included in the estimation of the loss of 
UPB due to property value deterioration.
---------------------------------------------------------------------------

    To measure average (performing loan) equity, the property value 
underlying each defaulting mortgage was adjusted using the change in 
the (Census division) OFHEO HPI from origination to the last-paid-
installment date, and using loan amortization schedules.\236\ This 
adjustment provides average expected equity for each loan, if it were 
performing. But these loans are not performing, and rather than having 
average house price growth, they will generally have lower-than-average 
house price growth. In fact, defaulting loans come from the lower tail 
of the equity distribution, so the statistical analysis must capture 
just how far into the tail defaulting loan properties will be, on 
average. OFHEO analyzed several measures of the house price 
distribution to find which gave the best prediction of the difference 
between average performing loan equity and average non-performing loan 
equity. The best predictor was the z-score, identifying the distance 
between the expected (performing loan) house price and the (actual 
defaulting) loan balance. The z-score transforms the actual difference 
between (expected) house price and (actual) loan balance into the 
number of standard deviations there are between the two values, where 
the standard deviation is of house prices in the Census division. The 
z-score tells how far below the average property value growth in the 
Census division must the growth of any individual property value be, 
before all borrower equity is eliminated. The difference of actual 
growth of defaulting loans from average growth for performing loans 
will be larger than this, on average, because the z-score distance 
gives the minimal difference needed to eliminate borrower equity. The 
z-score equation is:
---------------------------------------------------------------------------

    \236\ The last-paid-installment (LPI) month is the month 
directly prior to the month of default, when the first payment is 
missed. Loan amortization ends at LPI, and because the HPI index is 
updated quarterly rather than monthly, the choice of LPI month or 
default month for loan seasoning is immaterial.
[GRAPHIC] [TIFF OMITTED] TP13AP99.013

[GRAPHIC] [TIFF OMITTED] TP13AP99.227

    In their continuous rate forms, the cumulative growth rate factors 
are found by taking the logarithm of the HPI, as is done here. The log 
of HPI gives average price appreciation, and the difference between 
that and the log of the loan balance, B, gives the expected loan equity 
due to price appreciation, downpayment, and amortization.\237\
---------------------------------------------------------------------------

    \237\ Taking the logarithm of B transforms owner-invested equity 
(downpayment plus amortization) into an implied HPI growth rate 
factor. It is the cumulative (negative) growth of HPI necessary to 
eliminate all positive equity in the property. By transforming B 
into its continuous rate counterpart in this fashion, the z-score 
variable can measure the amount by which the growth of property 
value on loan properties must be less than the average growth rate 
of performing loans before default is a real possibility (the point 
of zero equity). The regression then measures the relationship 
between actual below-normal growth on REO properties and the 
minimumly required below-normal house price growth needed to trigger 
default.
---------------------------------------------------------------------------

    These standardized distances, or z-scores, are the key values used 
to compute the expected negative property equity (as a percent of the 
outstanding loan balance) when a foreclosed property is sold. Larger z-
scores reflect some combination of large downpayments, loan 
amortization, and high levels of (average) house price growth since 
loan origination. In these circumstances, loans that do default should 
have relatively good rates of property sale proceeds as a percent of 
the mortgage UPB (small rates of negative equity). In other 
environments, where z-scores are small, there are low rates of 
appreciation in the market, and/or low downpayments and a lack of 
significant amortization. The small z-score indicates that there is a 
wide range of property values in the market area that are below the 
loan balance. Therefore, REO sale proceeds will be low and the negative 
property equity will be high.
    The statistical equation used to predict negative property equity 
(L) was estimated using ordinary least squares (OLS) regression of 
actual rates of UPB loss on the z-scores computed for each loan. The 
regression dataset was limited to historical REO observations where 
(-0.50  zt  4.0), because sample sizes 
outside this range were very thin.\238\ Log-transformed values of 
negative property equity (ln(L) + 1)) were used in the regression to 
account for a change in the relationship between negative equity and z-
scores as those values change. The estimated regression equation is:
---------------------------------------------------------------------------

    \238\ In stress test application, outliers are given predicted 
equity loss values measured at the boundary points of the z-score 
range employed in the regression.

[[Page 18191]]

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[GRAPHIC] [TIFF OMITTED] TP13AP99.228

    One-half the regression variance (0.029104) is added to the 
regression equation to provide the median-to-mean adjustment factor for 
log-normal models.\239\ The result is:
---------------------------------------------------------------------------

    \239\ The logarithmic equation used in the regression implies a 
lognormal distribution of potential negative equity values around 
predicted values. The point estimates from the regression, 
therefore, produce median rather than mean value estimates of loss 
of principal balance. The adjustment to arrive at the mean is the 
additive constant (0.029104), one-half the variance of the 
regression residuals.
[GRAPHIC] [TIFF OMITTED] TP13AP99.015

so that:
[GRAPHIC] [TIFF OMITTED] TP13AP99.016

    The low R-squared value for the regression indicates a wide 
variance of actual loss rates around the average, predicted rates. 
OFHEO has analyzed this variance and believes that using the simple 
regression equation that captures average loss rates at each z-score 
value is more appropriate for the stress test than is a more complex 
model that would capture deviations around that average loss rate. 
Average rates provide an appropriate simplification because loss 
severity rates will be applied to groups of loans.
    The boundary values of L are computed at the boundary points of z 
used in the regression sample, 4.0 and -0.5. When z = 4.0, L = -0.04. 
This suggests that, on average, REO sales prices are 4 percent higher 
than the mortgage UPB in areas with significant house price 
appreciation and/or for loans that have substantial amortization. That 
is, the average default (and there will be relatively few) will 
actually have a small amount of positive equity, though generally not 
enough to pay the costs of selling the property. At the other extreme, 
where z = -0.5, the predicted value of L = 0.36. This is a situation 
where average property values on performing loans are 36 percent below 
their associated mortgage balances. This extreme was reached in several 
areas of the country at various times during the study period. Such a 
loss of loan principal can cause the total loss severity to exceed 60 
percent of UPB.

b. Foreclosure Expenses

    Foreclosure expenses vary principally by property State and by the 
rate of bankruptcy filings among defaulted borrowers.\240\ The average 
expense rate in the historical observation period is five percent of 
UPB. Unlike other loss components, this component is based solely on 
Fannie Mae experience because Freddie Mac did not break out foreclosure 
expenses from REO expenses in its data systems.
---------------------------------------------------------------------------

    \240\ To process foreclosures when defaulting borrowers file for 
Bankruptcy Court protection requires further legal expenses to gain 
release from the bankruptcy ``stay'' on debt collection actions.
---------------------------------------------------------------------------

c. REO Holding and Disposition Expenses

    Property (REO) holding costs include such items as property 
maintenance, utilities, property taxes, and hazard insurance. OFHEO 
calculated the average total REO holding expenses, plus selling costs 
(principally, realtor fees), less miscellaneous revenues to produce a 
final REO expense loss severity factor of 13.7 percent.\241\
---------------------------------------------------------------------------

    \241\ As noted earlier, the Freddie Mac foreclosure expense rate 
is imputed from the Fannie Mae experience (five percent). Therefore, 
the REO holding costs used to create the average rate shown here use 
total expense for Freddie Mac less imputed foreclosure expense for 
Fannie Mae.
---------------------------------------------------------------------------

d. Time Frames

    There are two time frames of interest: time from default to 
foreclosure completion, and time from foreclosure completion to 
property disposition. A mean expected value for each of the time 
periods of interest was calculated from BLE data. The mean benchmark 
foreclosure time (period from default to foreclosure) was 13 months. 
The mean benchmark REO/property sale time was seven months. These time 
frames are used in the stress test to discount the various default-
related cash flows to the month of default.
5. Consistency With the Benchmark Loss Experience
    The equation for negative equity of defaulted loans (equation 14) 
was estimated on all historical REO experience of the Enterprises. 
Using this broad range of data assured that the equation would be 
appropriate for loans entering the stress test with a wide range of 
loan amortization and cumulative HPI experience. The equation used in 
the stress test includes an adjustment that calibrates the results to 
the BLE.
    The procedure for calibrating equation 16 to the benchmark 
experience parallels the procedure used by OFHEO to calibrate the 
single family default equations to the BLE. A database of defaulted 
loans meeting benchmark criteria was input into the negative equity 
equation to compute the projected negative equity, by loan. The z-score 
variable values were computed by assuming that all loans originated in 
the first quarter of 1984, using the West South Central HPI series, for 
purposes of assigning house price appreciation rates. These predicted 
rates of negative equity were then averaged by Enterprise, using UPB as 
a weighting factor. Finally, a simple average of these Enterprise 
averages was computed to arrive at a mean expected value for the 
benchmark REO database.

[[Page 18192]]

    This final mean rate of negative equity on defaulted loans was then 
compared with the actual, historical mean rate across the two firms' 
benchmark experience. The average projected rate of negative equity 
using equation 16 and this averaging method was 21.30 percent. The 
actual historical experience average was 31.64 percent. The difference, 
10.34 percent, reflects the nature of the benchmark experience: that 
defaulting benchmark loans tended to have larger losses, on average, 
than did loans from other regions of the country that experienced the 
same housing market conditions. The adjusted negative equity equation 
is:
[GRAPHIC] [TIFF OMITTED] TP13AP99.017

    Proceeds from REO sale are then computed as one minus the projected 
negative property equity for the defaulting loans in each loan group.
6. Application to the Stress Test
    Stress test application of loss severities begins with the results 
of the statistical analysis of severity components discussed here, but 
then adds components for loss of loan principal, servicer claim 
payments, mortgage insurance, and seller/servicer recourse. OFHEO's 
approach is to account for all default related cash flows at one of 
three points in time: 120 days delinquency, foreclosure, and property 
disposition. The stress test then calculates the effective loss 
severity rate as a net present value of all cash flows, in the month of 
loan default. The month of default is one month after the last paid 
installment (LPI) date, the month of the first missed payment.
    There is a difference in the treatment of sold and retained loans 
when computing stress test loss severity rates. For retained loans, 
defaulting UPB is not a cash outlay and, therefore, is not discounted. 
For sold loans, however, the defaulting UPB represents the current 
expense of repurchasing a defaulted loan from a security pool. It is, 
therefore, a cash-flow element that should be discounted.\242\ This 
expense is normally incurred in the fourth month of default. Sold loans 
in default also involve four months of interest passthroughs to the 
investors while the loans remain in the security pools. The interest 
passthroughs are not immediate expenses of the Enterprises because they 
are initially matched by passthroughs made by the seller/servicers to 
the Enterprises. However, all post-default interest payments received 
by the Enterprises are reimbursed to servicers in the post-foreclosure 
claim filing. Therefore, all interest passthroughs between seller/
servicers and Enterprises are ignored. Only the passthrough by the 
Enterprise to security holders is counted as an expense in the stress 
test, and it is included with the seller/servicer claim payment at time 
of foreclosure.
---------------------------------------------------------------------------

    \242\ Such loans become part of the Enterprise retained 
portfolios once they are bought out of the security pools.
---------------------------------------------------------------------------

    The stress test provides that, at the time of foreclosure, the 
Enterprises make servicers whole for expenses incurred on the loan and 
property, including foreclosure costs, and receive proceeds from any 
available mortgage insurance. When mortgage insurance is present, 
mortgage insurance payments will generally be larger than the servicer 
claim payment and provide net inflows of funds to the Enterprises at 
foreclosure.
    Also, any available seller/servicer recourse is applied to reduce 
the final loss severity rate. There are some smaller sources of credit 
enhancements that further reduce Enterprise losses, and these are added 
once dollar losses are computed in the cash flow component of the 
stress test.\243\
---------------------------------------------------------------------------

    \243\ These lesser sources of credit enhancements are items 
where the amount of recourse available to the Enterprises is not a 
function of per loan losses, but rather it is available in total 
dollar amounts for pools of loans.
---------------------------------------------------------------------------

7. References
Berkovec, James A., Glenn B. Canner, Stuart A. Gabriel, and Timothy 
Hannan. 1998. Discrimination, Competition, and Loan Performance in FHA 
Mortgage Lending, Review of Economics and Statistics, forthcoming.
Capone, Charles A. and Yongheng Deng. 1998. ``Loss Severities and 
Optimal Put Exercise: An Examination of Negative Equity in Mortgage 
Foreclosure,'' unpublished manuscript. OFHEO: Washington, DC, January 
1988.
Clauretie, Terrence. 1990. ``A Note on Mortgage Risk: Default vs. Loss 
Rates,'' AREUEA Journal 18 (2), 202-206.
Crawford, Gordon and Rosenblatt, Eric. 1995. ``Efficient Mortgage 
Default Option Exercise: Evidence from Loss Severity,'' Journal of Real 
Estate Research 19 (5), 543-555.
Kau, James B. and Donald C. Keenan. 1993. ``Transaction Costs, 
Suboptimal Termination, and Default Probabilities for Mortgages,'' 
AREUEA Journal 21(3), 247-63.
Kau, James B. and Donald C. Keenan. 1997. Patterns of Rational Default, 
unpublished working paper, University of Georgia.
Lekkas, Vassilis, John M. Quigley and Robert Van Order. 1993. ``Loan 
Loss Severity and Optimal Mortgage Default,'' AREUEA Journal 21 (4, 
Winter), 353-372.

D. Multifamily Default/Prepayment

1. Introduction and Conceptual Framework
    This section describes how OFHEO developed its model of multifamily 
default and prepayment rates for use in the risk-based capital stress 
test. The same theory that underlies the single family default/
prepayment models, financial options theory, also underlies OFHEO's 
modeling of mortgage performance for multifamily loans. However, the 
single family approach is modified to account for the importance of 
property cash flows in the default decisions of investors. This 
theoretical framework treats mortgage terminations as a function of 
their financial value to the borrower. Both the single family and 
multifamily default/prepayment models also use a multinomial logistic 
specification to estimate the impact of explanatory variables on 
default and prepayment rates. Beyond these similarities in general 
approach, however, there are significant differences in the specifics 
of model construction and estimation.
    Many of these differences reflect special features of multifamily 
mortgages. For these loans, the borrowers are all investors, and that 
affects the determinants of credit risk. Two key financial ratios are 
used in commercial mortgage underwriting: the DCR and the LTV. DCR is a 
property's net operating income (NOI) divided by the mortgage 
payment.\244\ DCR indicates how much cash there is available for loan 
repayment after operating expenses are paid. LTV is the ratio of the 
UPB to the value of the property; it measures

[[Page 18193]]

borrower equity.\245\ Lenders concentrate on these two ratios at loan 
underwriting, and all major credit rating agencies start their analysis 
of the credit support levels needed to receive various rating grades 
with the DCR and LTV values of the loan collateral.
---------------------------------------------------------------------------

    \244\ NOI is a measure of the differernce between full potential 
rent at market prices and operating expenses (including vacancy 
losses).
    \245\ Commercial loan underwriting also includes examinations of 
borrower credit, servicing capability, site and engineering reviews, 
and cost certifications for new construction. Market condition 
reports are part of the appraisal process used to estimate LTV at 
loan origination.
---------------------------------------------------------------------------

    Multifamily mortgage modeling should also recognize the special 
features that differentiate commercial loans from single family 
residential loans. Commercial loans have prepayment restrictions, 
usually in the form of yield maintenance clauses, that severely reduce 
the value of refinancing during the early years of a mortgage. 
Commercial loans are also dominated not by fully amortizing 30-year 
loans, but by balloon mortgages with maturities of up to 15 years. 
These two product distinctions--yield maintenance and balloon terms--
create different borrower incentives and different mortgage performance 
patterns for multifamily mortgages.
    Previous research on multifamily mortgage performance has generally 
made simplifying assumptions to avoid having to deal with all of these 
issues in one model. First, research has tended to ignore DCR and only 
concentrate on LTV. Even then, without readily available property value 
indexes, researchers have not updated LTV over time to capture local 
market conditions.\246\ Some studies have captured property cash flows, 
but they omitted LTV and had no mechanism for updating property cash 
flows for projection purposes.\247\ One study that recognized the need 
for both DCR and LTV for predicting default rates, defined them to be 
perfectly correlated so that only one financial variable needed to be 
included in the model.\248\ Another shortcoming of past research has 
been that default and prepayment have not been analyzed together.\249\ 
Either defaults are assumed not to matter because of agency guarantees, 
or else prepayments are ignored because of yield maintenance terms. 
Most studies model defaults without prepayments, but prepayment studies 
are starting to appear, with three in 1997 and one in 1998.\250\ In 
both default and prepayment studies, little work has been done to 
understand the dynamics of yield maintenance and balloon terms.\251\ 
But even with all of these limitations in current research, the 
greatest concern is that researchers most often resort to pooling 
multifamily mortgages with loans on other commercial property types in 
order to have sufficient sample sizes.\252\
---------------------------------------------------------------------------

    \246\ Vandell (1992) and Vandell, et al. (1993) develop models 
of commercial mortgage default that update LTV over time using a 
national property-value index, along with the property-value 
diffusion process introduced by Foster and Van Order (1984) for 
single family mortgages.
    \247\ See ICF (1991) and Pedone (1991). These studies adapt the 
work of Edward Altman (1981, 1983) to predict corporate bankruptcy 
to model multifamily defaults. Capone (1991) discusses the 
application of bankruptcy models to multifamily mortgages, and 
provides a review of this literature. A related line of literature 
discusses the relationship between lender and borrower in the 
default/bankruptcy process. Kahn (1991) and Mahue (1991) study the 
impact of foreclosure laws on the balance of borrower and lender 
bargaining strength at these crucial junctures. Riddiough and Wyatt 
(1994a, 1994b) explore the power of lender signals of intent to 
pursue debt collections on distressed-loan foreclosure.
    \248\ Abraham (1993b).
    \249\ The first known attempt outside of OFHEO to model default 
and prepayment rates simultaneously was by Boyer, Follain, Ondrich, 
and Piccirillo (1997), who studied FHA insured mortgages.
    \250\ Abraham and Theobald (1997), Elmer and Haidorfer (1997), 
Follain, et al. (1997), and Capone and Goldberg (1998).
    \251\ In a theoretical pricing model, Kau, et al. (1990) do 
attempt to show how prepayment restrictions impact both default and 
prepayment options with balloon mortgages.
    \252\ The lack of historical data has often been cited as a 
major obstacle to research on multifamily and commercial loan credit 
risk (DiPasquale & Cummings, 1992; Standard & Poors, 1993; and 
Vandell, et al., 1993). Studies that combine multifamily with other 
commercial mortgage types include Vandell (1992), Vandell, et al. 
(1993), Barnes and Gilberto (1994). Studies that use only 
multifamily data tend to model FHA-insured loans (Goldberg, 1994; 
ICF, 1991; Follain, et al., 1997). Exceptions to this include 
Abraham (1993a, 1993b), who used multifamily loan data from Freddie 
Mac to study defaults, and Abraham and Theobald (1997), who use 
Freddie Mac data to model multifamily prepayment rates. Elmer and 
Haidorfer (1997) use Resolution Trust Corporation data to study 
multifamily prepayment rates. Researchers at OFHEO have published a 
default study based on Enterprise data (Goldberg and Capone, 1998).
---------------------------------------------------------------------------

    The broad conceptual framework chosen by OFHEO corresponds to the 
dominant paradigm in mortgage research, financial options theory. 
Studies that apply financial options theory to commercial mortgage 
performance have generally emphasized the role of borrower equity (LTV) 
in default rate estimation, but have not seriously modeled the role of 
cash flows (DCR).\253\ However, because both DCR and LTV are critical 
credit risk dimensions, an appropriate multifamily mortgage performance 
model should also treat cash flows and equity as essential 
elements.\254\
---------------------------------------------------------------------------

    \253\ Even theoretical ``pricing'' models that simulate default 
rates on a pool of newly originated mortgages make simple 
assumptions that cash flow to the property owner is a fixed 
percentage of property value (Titman and Torous, 1989; Kau, Keenan, 
Epperson, and Muller, 1987 and 1990). They also treat cash flow as 
something negative (detracts from potential future property value) 
rather than something positive to the investor/owner/borrower.
    \254\ Abraham (1993b), Goldberg (1994), and Quercia (1995) have 
all questioned the sufficiency of net equity as a default trigger.
---------------------------------------------------------------------------

    For the default option to be in the money, the property must have 
both negative equity (LTV>1) and negative cash flow (DCR<1). The two 
sources of income for an investment property owner are rental (current) 
income and capital gains. Rental income can be thought of as dividend 
payouts from the property. Capital gains result when the property is 
sold. The owner holds the property until the expected annual rate of 
return from both dividends and capital gains becomes less than the 
return that could be earned by selling the property and investing the 
proceeds into another investment. However, if the rental market 
declines, and property equity becomes negative, then default becomes a 
viable option. This option will not be exercised as long as the 
dividend payout is positive. If property owners/borrowers were to 
default in the presence of positive cash flows, they would give up 
valuable cash flow streams. Therefore, default is only optimal if both 
equity and cash flow are negative. This implies that the dual 
condition, LTV> 1 and DCR<1, is required for default to occur.\255\
---------------------------------------------------------------------------

    \255\ The wealth-maximizing borrower should default if the 
property expects to have negative equity and negative cash flow from 
this point on. If there are negative cash flows, delaying default 
would lower wealth. If negative equity and negative cash flow were 
expected to be only temporary conditions, default would not be 
optimal. In principle one should incorporate expectations regarding 
rental markets and interest rates, simulate wealth over time, and 
have the borrower default only if it maximizes wealth over some 
long-run investment horizon. This was viewed as an overly complex, 
expensive, and therefore unfeasible approach. Theory 
notwithstanding, researchers typically construct the default option 
value variable using just current year information. This is also the 
approach taken by OFHEO. For relevant theoretical studies, See Kau 
et al. (1987, 1990), Brennan and Schwartz (1985), Dyl and Long 
(1969), Joy (1976), and Robichek and VanHorne (1967).
---------------------------------------------------------------------------

    Prepayment options are in some ways simpler and in others more 
complex than default options. The simplicity arises because the 
financial value of prepaying a mortgage is directly measured by the 
mortgage premium value, the difference between the present value of 
future mortgage payments discounted at the current note rate, and 
present value of those same payments discounted at the current market 
rate. When interest rates fall, there is negative value to holding onto 
the existing mortgage, measured by a negative mortgage premium value. 
However, measuring the premium value itself is complex because of yield 
maintenance and balloon terms. When a

[[Page 18194]]

fixed-rate loan is under yield maintenance, it may refinance, but it 
will not accrue any value from the transaction until the yield 
maintenance period expires.\256\ With balloon loans, there is the added 
uncertainty surrounding the contractual requirement to find new funding 
at loan maturity. Risk averse borrowers, therefore, may desire to 
refinance in the pre-balloon period even if the call option is not in 
the money.
---------------------------------------------------------------------------

    \256\ ARM loans have minimal penalties, and they have prepaid 
much more often in the early years after loan origination.
---------------------------------------------------------------------------

    An additional consideration for modeling prepayment speeds is that 
investors desire to leverage their investments to maximize return on 
equity. Interest rate spreads do not, therefore, provide the only 
incentive for refinancing a mortgage. To maximize leverage requires 
maximizing LTV ratios, within bounds set by lenders. Over time, 
investors will engage in cash-out refinancings in order to rebalance 
the ratio of debt to equity in the property. This second prepayment 
incentive can be captured by the LTV of the mortgage.
    In modeling multifamily mortgage default rates, OFHEO distinguishes 
among the various programs of the Enterprises. Conventional multifamily 
loan purchases by the Enterprises began in 1983, and include ``cash'' 
and ``negotiated'' programs. Under the cash programs, the Enterprises 
purchased newly originated individual loans underwritten according to 
their own guidelines. Historically, most of these loans were retained 
in the portfolios of the Enterprises. Some ``cash'' loans were swapped 
for MBS, and this type of transaction is becoming more common. In a 
negotiated transaction, an Enterprise swaps pools of seasoned (i.e., 
aged and performing) loans for securities. These loans need not meet 
the underwriting guidelines of cash programs, and they are priced 
according to the risk of the loans in the pool. In negotiated 
transactions, unlike cash purchases, an Enterprise often requires 
credit enhancement from the seller/servicer to cover expected credit 
losses.
    The initial cash programs exposed the Enterprises to significant 
credit risk in the late 1980s and into the 1990s. This exposure was due 
to generous appraisal practices used in the 1980s and to other 
significant weaknesses in those programs that do not exist today. 
Fannie Mae changed its cash program in 1988. Freddie Mac continued to 
build a portfolio of less-than-investment-grade mortgages through 1990. 
The poor performance of this portfolio led to a three-year moratorium 
on Freddie Mac's new purchases of multifamily loans, and a complete 
overhaul of the multifamily operations of the Enterprise.
    Prepayment rates were modeled by loan characteristics product type 
rather than program type. This breakdown captures the differences in 
financial incentives to prepay that exist when yield maintenance 
penalties are or are not in effect, and the impact on defaults of 
balloon mortgage maturity. Balloon maturity is a significant 
multifamily modeling issue for the stress test because, in an up-rate 
interest rate environment, balloon loan borrowers are often required to 
pay off the existing mortgage and refinance, at much higher interest 
rates than property financials are currently supporting. In order to 
refinance at the balloon point in the up-rate scenario, property income 
must be higher than the minimum necessary to qualify for a new loan 
under the original interest rates. Therefore, it is important to model 
both the expected default and payoff rates of loans at balloon maturity 
for the stress test.
    Section 2 of this supplementary material on multifamily default/
prepayment provides a review of the historical data used to estimate 
the statistical models, and section 3 reviews the statistical 
procedures employed. Section 4 completes the description of the 
statistical model with explanations of the development of the 
explanatory variables. Section 5 presents and reviews the results of 
statistical estimations, and section 6 concludes with a discussion of 
how the estimated statistical equations are applied in the stress test.
2. Historical Data

a. Enterprise Loan Records

    OFHEO used the combined historical experience of the Enterprises, 
1983-1995, to estimate the statistical model of default and prepayment 
rates. This experience provided a large and rich data base that 
encompasses three different programs: the initial cash purchase 
programs that had high default rates; negotiated purchase (or 
transactions) programs where securities were swapped for pools of 
seasoned and performing mortgages; and new cash purchase programs that 
corrected flaws in the original programs and have experienced low 
default rates.
    The historical data includes 35,759 conventional multifamily 
loans.\257\ After eliminating missing or erroneous records, the sample 
includes observations on 21,994 loans: 12,845 from Freddie Mac and 
9,149 from Fannie Mae. Of these, 61 percent are cash purchases and 39 
percent are negotiated purchases. The final cash purchase sample is 
more complete than the negotiated purchase sample because, in 
negotiated programs, the Enterprises have relied more on buying 
seasoned portfolios with (limited) credit risk recourse to the seller/
servicer, rather than on gathering enough property financial 
characteristics to re-underwrite the loans.\258\
---------------------------------------------------------------------------

    \257\ Fannie Mae has maintained a portfolio of FHA-insured 
multifamily mortgages over time. OFHEO chose not to model 
performance of these loans, but rather to assign default and 
prepayment rates according to conventional loans with similar 
features. Because FHA pays for nearly 100 percent of default losses, 
the stress test imposes no credit losses on FHA-insured mortgages on 
the stress test.
    \258\ Ninety percent of cash purchases are retained in the final 
sample, while only 41 percent of negotiated purchases had enough 
loan characteristics data to be kept in the sample. For the 41 
percent of negotiated purchase loans in the sample, DCR values at 
time of acquisition were estimated by OFHEO by first estimating net 
operating income (NOI) as NOI=value at origination divided by an 
estimate of the average CAP rate multiplier for the year, divided by 
the mortgage payment amount.
---------------------------------------------------------------------------

    The database was expanded by creating annual observations from loan 
acquisition to the termination year, or to 1995 if no termination 
occurred. The loan-year file includes 89,577 loan-year observations for 
cash purchases, and 59,415 observations for negotiated purchases. Cash 
purchases appear in the database with origination years from 1983 to 
1995. The negotiated loans, however, have origination years as early as 
1970 because they were often highly seasoned at time of acquisition. 
Annual observations are used, rather than monthly or quarterly 
observations, because of the relatively small number of multifamily 
termination events. If quarterly or monthly event histories were used, 
there would be significant numbers of time periods in which there were 
no terminations.
    To avoid any possible statistical bias resulting from not having 
records of loan terminations prior to 1983, negotiated purchase loans 
enter the database starting in the acquisition year, rather than the 
origination year. But they enter at their proper age and are not 
treated as new originations at the time of acquisition. The same issue 
of potential ``left censoring'' bias also appears for certain cash 
purchase programs, where the Enterprises did not begin to maintain 
systematic records of loan terminations until 1991. For such programs, 
the loans do not enter the statistical estimation sample until 
1991.\259\
---------------------------------------------------------------------------

    \259\ The left-censoring bias would result if the statistical 
model used complete loan-history records for all loans, when some 
groups of loans only enter the sample if they survive to a certain 
point (e.g., time of acquisition by the Enterprise). If the sample 
were not censored at the acquisition point, the model could severely 
underestimate the rates of loan termination in the early years of a 
mortgage.

---------------------------------------------------------------------------

[[Page 18195]]

    For cash loans, the default outcome of record is a foreclosure or 
foreclosure alternative that still provides for the property to be 
liquidated.\260\ For most Fannie Mae negotiated purchase loans, 
however, the default event of record is a 90-day delinquency. This is 
because, for Fannie Mae negotiated transactions, the loan is 
repurchased by the seller/servicer if it becomes 90-days delinquent. 
The seller/servicer then bills Fannie Mae for resolution costs, and 
these are deducted from a limited recourse pool originally established 
with funds from the seller/servicer at time of acquisition. OFHEO 
recognizes that 90-day delinquencies cannot be treated as full default 
events, and makes adjustments in the statistical model.
---------------------------------------------------------------------------

    \260\ Foreclosure alternatives include third party sales where a 
``third party'' purchases the property at the foreclosure auction; 
short sales, where the Enterprise finds a buyer for the property 
prior to completion of foreclosure; and note sales, where the 
mortgage itself is sold to another investor.
---------------------------------------------------------------------------

b. Rents and Vacancies

    OFHEO uses a unique approach to property valuation that uses local 
market indexes of rent growth rates and vacancy rates to update net 
operating income, and through that, update DCR and LTV over time. Rent 
growth rates came from the residential rent component of the CPI for 
each of the four Census regions, and for the 29 MSAs covered by Bureau 
of Labor Statistics (BLS) surveys. Most MSA level CPI series produced 
by BLS start in 1970, but some do not begin until the 1980s. The 
regional CPI series are available beginning in 1978, so percent changes 
for these can only be computed starting in 1979. To capture rent growth 
rates for each year, partial MSA series were completed with regional 
series starting in 1979 and national series before that. The regional 
series themselves were also filled in for the pre-1979 period with 
percent changes in the national CPI residential rent series.
    Vacancy rates were obtained from the Bureau of the Census H-111 
series. These are available for the same MSAs as is the CPI residential 
rent series (back to 1970), and for Census regions, and, beginning in 
1986, for the 50 States plus the District of Columbia.\261\ As with 
rent growth rates, the most disaggregated index available was used for 
each loan, in each calendar year.
---------------------------------------------------------------------------

    \261\ Census also added more MSAs starting in 1986. These were 
not used in OFHEO's statistical analysis.
---------------------------------------------------------------------------

c. Tax RatesOFHEO required tax rate data for calculating the 
present value of depreciation writeoffs (see discussion of the 
explanatory variable, DW, below). In order to compute weighted 
average tax rates, OFHEO used Internal Revenue Service (IRS) data 
on the income distribution of taxpayers with net capital gains. For 
1983-90, data on adjusted gross income for taxpayers with net 
capital gains were obtained from the IRS publication, Individual 
Income Tax Returns (annuals). For 1991-95, data were obtained from 
IRS, Statistics of Income Bulletin (quarterly). These income-class 
weights were used to compute weighted average tax rates for both 
capital gains and ordinary income.

    The marginal tax rate on ordinary income used here is for Married 
Filing Jointly taxpayers (Schedule Y-1). Five percent was added to the 
Federal tax rate for State income taxes. Schedule Y-1's for 1983-95 
were obtained from Internal Revenue Service, Package X (annual 
publications 1983-95). Data on capital gains tax rates were obtained 
from IRS's Package X, for 1983-95. No adjustment was made for State 
taxes on capital gains.
    Data on depreciation schedules is for newly constructed residential 
rental property, from the IRS publication, Depreciation 1992, 
Publication 534. This publication includes accelerated schedules for 
years 1983-92. Accelerated depreciation was assumed in years in which 
it was an option. Because there were no changes in the tax code 
affecting depreciation after 1992, the schedule for 1992 was used for 
1993-95.
3. Statistical Estimation
    The statistical estimation involves binomial logistic regressions 
of subsets of the data. There are two separate regressions for default 
rates and five separate regressions for prepayment rates. This 
breakdown accommodates programmatic differences between cash and 
negotiated purchases in the default equations, and the changing nature 
of prepayment incentives across various products and loan terms. The 
results are matched together so that the end result is trinomial 
logistic probability equations that provide the same result as if 
defaults and prepayments were estimated simultaneously for each loan 
program and product.\262\
---------------------------------------------------------------------------

    \262\ This is the three-choice logit model, though the more 
generic model is known as the multinomial logit, or MNL.
---------------------------------------------------------------------------

    The logistic model is founded on assumptions that the utility of 
each borrower payment choice--make payment, prepay, or default--is a 
function of its contribution to wealth and that, each observation 
period, borrowers make the choice that maximizes wealth. The 
regressions compute weights (coefficients) that estimate the influence 
of each explanatory variable on the net wealth effect of one choice 
over another. These models estimate the log-odds of choosing a mortgage 
termination over continuing to make loan payments as a function of the 
explanatory variables. In particular,
[GRAPHIC] [TIFF OMITTED] TP13AP99.018

and
[GRAPHIC] [TIFF OMITTED] TP13AP99.019


[[Page 18196]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.229


    And the resulting equations for calculating probabilities are 
transformations of these equations:
[GRAPHIC] [TIFF OMITTED] TP13AP99.020

and
[GRAPHIC] [TIFF OMITTED] TP13AP99.021

    If X and Y are matrices of all event-history records, then the 
resulting probabilities will be (column) vectors of estimated 
probabilities for each of these records, for each observed time period. 
Because of the relatively small number of loan defaults in the data, 
OFHEO used annual observations to estimate the equations. Economic 
variables are averages for each calendar year, and the logistic 
equations estimate probabilities of default and prepayment for all 
loans surviving to the beginning of the next year.
    The probabilities of default and prepayment are interdependent, and 
normally the equations would be estimated using simultaneous equations 
methods. However, because there are two default equations and five 
prepayment equations, doing so would be quite complex. Following Begg 
and Gray, OFHEO estimated the system using single equation methods in 
which separate binomial log-odds equations are estimates for default 
and prepayment.\263\
---------------------------------------------------------------------------

    \263\ See Begg and Gray (1984). To do this, one must be sure to 
censor competing termination events from the regression samples. 
That is, for default rate log-odds estimation, all prepayment 
observations must be censored in the period of the prepayment (and 
vice versa). This censoring assures that the estimation is of the 
log-odds of defaulting (or prepaying) versus remaining current on 
the mortgage. The underlying principle of logistic regression 
analysis that allows for this approach to modeling the competing 
risks of default and prepayment is called the independence of 
irrelevant alternatives. This principle means that logistic analysis 
assumes that the log-odds of default versus remaining current are 
not influenced by the log-odds of prepaying versus remaining 
current.
---------------------------------------------------------------------------

4. Explanatory Variables
    The multifamily mortgage performance model has separate sets of 
explanatory variables for default and prepayment analysis. They are 
described separately here.

a. Default Equations

    OFHEO estimated two separate logit default equations, one for cash 
purchases and one for negotiated purchases. This decomposition serves 
three purposes. First, significant numbers of negotiated purchase loans 
did not enter the Enterprise portfolios until after the Tax Reform Act 
of 1986. That statute greatly changed the value of depreciation 
allowances to new purchasers of investment real estate. OFHEO desired 
to model the effects of tax law changes on default rates, but could 
only do this with the cash purchase loans, where there are significant 
numbers of observations both before and after tax reform. The second 
reason for separating cash from negotiated purchase loans is that 
negotiated loans did not undergo the same change of quality as did cash 
purchases. It is easier to separate the effects of movements by the 
Enterprises from original to new cash-purchase programs if these are 
isolated from the negotiated purchases for default analysis. A third 
reason for separating the two programs into two separate default 
equations is that the majority of negotiated purchase loans have 
seller/servicer repurchase provisions, which required use of 90-day 
delinquency as the default event of record. OFHEO decided that 
capturing the difference between 90-day delinquencies and full defaults 
was best achieved through an estimation that involved only negotiated 
purchases.
    Table 33 provides a list of the explanatory variables used in each 
default equation. Each variable listed in the Table will be described 
and developed more fully below.

[[Page 18197]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.221



(i) Joint Probability of Negative Equity and Negative Cash Flow

    The key explanatory variable in the default equations is the joint 
probability of negative equity and negative cash flow, which is defined 
as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.022

    A probabilistic measure is used because the exact financial 
condition of each mortgaged property, over time, is unknown. However, 
the equity and cash flow positions of the property at time of loan 
acquisition, and how local rents and vacancy rates changed over time 
are known. With this information, and reasonable assumptions regarding 
the dispersion of rent growth rates and vacancy rates across 
properties, the joint probability, JP, can be constructed. This 
variable is similar to the probability of negative equity variable used 
in the single family mortgage performance model, only here the variable 
begins with an index of growth rates of property net operating income 
(NOI), rather than an index of the growth rates of property value 
directly. OFHEO developed this approach for multifamily modeling 
because there are no property value indexes available, and it was not 
feasible to develop one with Enterprise data.
    Ideally, JP would capture all of the numerous factors affecting LTV 
and DCR, including rents, expenses, vacancies, special underwriting 
provisions (e.g., maintenance reserves), interest rates, and tax laws. 
OFHEO incorporated three important factors into the JP variable: rents, 
vacancies and interest rates. Because the actual property purchase year 
for current investors is unknown, the actual tax code affecting 
depreciation writeoffs is also unknown for each property. Therefore, 
OFHEO constructed a separate variable that captures changes in the 
value of tax benefits from property ownership to a new purchaser. 
Changes in property expenses are incorporated into JP by specifying 
that expenses are a constant ratio of rents.
(a) Creating Time Series for DCR and LTV
    The construction of JP first involves creating time series 
variables for DCR and LTV. Each of these can be shown to be a function 
of property NOI in each time period, t:
[GRAPHIC] [TIFF OMITTED] TP13AP99.023


[[Page 18198]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.230


and
[GRAPHIC] [TIFF OMITTED] TP13AP99.024

[GRAPHIC] [TIFF OMITTED] TP13AP99.231

    For commercial properties, appraisers use capitalization (``cap'') 
rate factors for estimating the present value of a future stream of 
property NOI.\264\ The cap rate multiplier for each loan at 
origination, M0, can be derived given three other variables: 
LTV0, UPB0, and NOI0. Because the cap 
rate multiplier is a function of interest rates, changes in interest 
rates over time will affect Mt and, through that, affect 
Vt and LTVt also. OFHEO collected data on cap 
rate multipliers at origination on Enterprise loans and the mortgage 
coupon rates on those loans.\265\ These data were used to estimate the 
elasticity of the cap rate multiplier with respect to interest rates, 
so that property values can be updated in response to interest rate 
changes. The estimated regression equation is:
---------------------------------------------------------------------------

    \264\ While the cap rate multiplier is used here to project 
property value from NOI, the cap rate itself is the reciprocal of 
the multiplier. So if, for example, a cap rate multiplier of 10 is 
implied from the property value (and the underlying NOI), the actual 
cap rate is 0.10. The cap rate on each individual property begins, 
like other appraisal techniques, with cap rates found on recent 
sales of comparable properties. Appraisers then incorporate an 
assessment of the duration and risk of the earnings on the 
particular property into the final cap rate used to project property 
value; a risky earnings stream will be penalized with a higher cap 
rate (lower multiplier).
    \265\ The choice of an interest rate series to use here was one 
of convenience, and does not materially affect the results.
[GRAPHIC] [TIFF OMITTED] TP13AP99.025

[GRAPHIC] [TIFF OMITTED] TP13AP99.232

    By estimating a double-log equation, the coefficient on the 
interest rate variable, rc,0, is the elasticity of the cap 
rate multiplier with respect to interest rate changes. This elasticity 
is used to project changes in Mt over time (since loan 
origination) as follows:
[GRAPHIC] [TIFF OMITTED] TP13AP99.026

where:
[GRAPHIC] [TIFF OMITTED] TP13AP99.233

and the factor used to update LTVt over time is then,

[[Page 18199]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.027


    Updating the DCRt and LTVt series requires a 
method for updating NOIt. NOIt can be expressed 
as a function of rents, operating expenses, and vacancy rates:
[GRAPHIC] [TIFF OMITTED] TP13AP99.028

[GRAPHIC] [TIFF OMITTED] TP13AP99.234

    For national data from annual surveys of apartments by the 
Institute for Real Estate Management (IREM), from 1970 through 1992, 
the average ratio of operating expenses to gross rents was 47.2 
percent. In computing values for NOIt, kt is held constant 
at 0.472. All properties must meet minimum occupancy (maximum vacancy) 
requirements before permanent funding is secured and the loans are 
purchased by the Enterprises. To estimate the models, the vacancy rate 
at origination is also held constant, in this case at the long-term 
average observed in Census vacancy surveys, 1970-1995: 0.0623. Thus, 
current values of NOI, relative to the value at loan origination, are 
calculated as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.029

Which reduces to:
[GRAPHIC] [TIFF OMITTED] TP13AP99.030

    The ratio of the dollar rents (RENTt/RENT0) 
is a rent index from the time of loan origination to time period t. 
Denoting this ratio as RPIt,:
[GRAPHIC] [TIFF OMITTED] TP13AP99.031

    If there has been no change in the vacancy rate since loan 
origination, so that vt = 0.0623, then the growth of net 
operating income equals the growth of rents since loan origination.
    With these formulas for updating the cap rate multiplier, 
Mt, and net operating income, NOIt, time series 
can be created for DCRt and LTVt.
[GRAPHIC] [TIFF OMITTED] TP13AP99.032

and
[GRAPHIC] [TIFF OMITTED] TP13AP99.033


[[Page 18200]]


For DCRt, the denominator of the update formula 
(PMTt/PMT0) (equation 32) will always equal 1.0 
for fixed-rate mortgages.

(ii) Construction of the JPt Variable

    Both RPIt and t are market indexes. 
The values for individual properties--RPIj,t and 
j,t--are not known, but can be assumed 
to be random variables that follow standard distributional forms, with 
mean values RPIt and t. To look at how 
the distribution of rent growth rates and vacancy rates affects the 
distribution of property level DCR and LTV values, it is convenient to 
use a logarithmic transformation of equation (31):
[GRAPHIC] [TIFF OMITTED] TP13AP99.034

where Zt = [1-2.15 (t-0.0623)] and 
RPIt is a rent index that equals one plus the growth of 
rents since loan origination. Zt can be interpreted as the 
percentage change in NOIt due to changes in the vacancy rate 
since loan origination, and RPIt is the percentage change in 
NOIt due to rent growth. If ln(Z) and ln(RPI) are normally 
distributed across properties, at any given point in time, then their 
sum has a bivariate normal distribution. This implies a bivariate 
normal distribution for ln(DCR) and ln(LTV), which provides the 
distributional form used to estimate the joint probability that DCR < 1 
and LTVt > 1 for any given property, JPt.
    Normality for ln(RPI) follows from the standard assumption that 
growth rates follow a lognormal diffusion process over time. Such a 
process is also foundational to the OFHEO HPI, which is used for single 
family mortgage performance analysis. With lognormal diffusion, the 
distribution of ln(RPIj,t), where j is a property index, is:
[GRAPHIC] [TIFF OMITTED] TP13AP99.035

[GRAPHIC] [TIFF OMITTED] TP13AP99.235

    If all apartment units can be assumed to have the same probability 
of being vacant, the distribution of vacancy rates across properties, 
within a geographic area, can be assumed to be binomial, with mean and 
variance parameters:
[GRAPHIC] [TIFF OMITTED] TP13AP99.036

[GRAPHIC] [TIFF OMITTED] TP13AP99.236

    The binomial distribution for apartment vacancies at the project 
level is bounded below by zero and skewed to the right, and because it 
can be approximated by a lognormal distribution with the same 
parameters. Thus, Zj,t, which is a linear transformation of 
vj,t, can be modeled with a lognormal distribution:
[GRAPHIC] [TIFF OMITTED] TP13AP99.037

    This allows ln(Zj,t) to be modeled with a normal 
distribution. Rewriting the parameters of Zj,t as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.038

we can write the parameters of the (normal) distribution of 
ln(Zj,t) as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.039


[[Page 18201]]


where the t subscripts for these parameters are dropped here and 
subsequently for clarity. Because both ln(DCRj,t) and 
ln(LTVj,t) are linear functions of the normally distributed 
random variables, ln(Zj,t) and ln(RPIj,t), 
ln(DCRj,t) and ln(LTVj,t) have a bivariate normal 
distribution, 
BV(1,2,1,
2,), where,
[GRAPHIC] [TIFF OMITTED] TP13AP99.040

    The correlation between ln(LTVj,t) and 
ln(DCRj,t) in the historical Enterprise data is used as an 
estimate of  (-0.5975). Unpublished data from the Bureau of 
Labor Statistics (BLS) suggests a value for 
2t of 7.5 percent. Alternative values 
between 5 and 15 percent were also considered, but the statistical 
model results (default rate equations) were insensitive to the value 
used for this variance.\266\
---------------------------------------------------------------------------

    \266\ This is because the variance of lnDCR and lnLTV is much 
more heavily influenced by the variance of the vacancy rate than the 
variance of the growth rate of RPI.
---------------------------------------------------------------------------

    The bivariate normal distribution defined by the parameters in 
equation 40 can be used to calculate the joint probability of negative 
equity and negative cash flow, JP. The joint probability is the 
bivariate (standard) normal distribution evaluated at particular 
boundary (cutoff) values for ln(DCR) and ln(LTV). The definition of 
JPj,t can be restated as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.041

which can be calculated using the bivarate normal distribution:
[GRAPHIC] [TIFF OMITTED] TP13AP99.042

where x and y are two standard normal random variates, each 
representing the possible values of the logs of DCR and LTV values on 
all apartment properties in a given geographic area, at a given point 
in time. The x and y values are standardized, which for DCR and LTV is 
accomplished by subtracting from them the log of the expected values 
for each property, 1,t and 2,t, 
and then dividing by the respective standard deviations, 
1,t and 2,t. The two limits of 
integration, a and b, are the standardized differences between the 
expected values for each property and the boundary conditions, which 
are the log of 1.00 for each. So, from equation 40 they are just:
[GRAPHIC] [TIFF OMITTED] TP13AP99.043

and
[GRAPHIC] [TIFF OMITTED] TP13AP99.044

(iii) Updating DCRt for Balloon and ARM Payment Shocks

    The joint probability variable, JPt, is given additional 
weight for balloon loans in the maturity year. Weaker loans will be 
unable to qualify for refinancing in the balloon year, especially if 
there is an increase in rates, which leads to more defaults at that 
point, for any given level of DCRt and LTVt. This 
effect should be a function of JPt. Balloon year

[[Page 18202]]

shock is added using a composite variable BJPt:
[GRAPHIC] [TIFF OMITTED] TP13AP99.045

where BYRt is a dummy variable equal to 1 if the observation 
is the balloon year, and 0 otherwise, and JPt is the joint 
probability of negative equity and negative cash flow. (The loan 
specific subscript, j, is dropped here for ease of exposition.) Due to 
the small number of balloon loans in negotiated purchase portfolios, 
this variable is only estimated in the default rate equation for cash 
purchase loans. In stress test application, the estimated coefficient 
for cash purchases is also used to predict default rates of negotiated 
purchase balloon loans in the maturity year.
    The Enterprises tend to extend balloon loans beyond maturity when 
properties cannot meet minimum qualification standards for a new loan, 
provided the borrower continues to make the monthly payment on the 
original mortgage. This possibility of what is called ``extension 
risk,'' the risk of loans not leaving the portfolio at the balloon 
point, has been documented by Elmer and Haidorfer (1997) and by Abraham 
and Theobald (1997). OFHEO also finds that in the Enterprise database a 
large percentage of loans are extended beyond balloon maturity. This 
model imposes payment shock for extended loans by updating the DCR to 
reflect what the borrower would be paying if the borrower refinanced 
the property. DCRt is updated after the balloon point by 
adjusting PMTt to reflect a new payment level commensurate 
with market interest rates for fixed-rate (fully amortizing) loans in 
the balloon year.
    ARMs are treated with similar DCR adjustments, except that the 
payment adjustment occurs annually.\267\ Fannie Mae and Freddie Mac 
purchased very few ARM loans through their cash programs, however there 
are significant numbers of negotiated transactions that are ARMs.
---------------------------------------------------------------------------

    \267\ Nearly all ARMs in Enterprise portfolios are indexed to 
the 11th District FHLB Cost of Funds, with monthly rate adjustments, 
semi-annual payment adjustments, and negative amortization 
provisions. The payment adjustment calculations here proxy for the 
full stress of partial payment adjustments and negative amortization 
by treating ARM loans as 5/1 products where annual payment changes 
are only limited by the lifetime and annual rate caps (5 and 1 
percent, respectively). This allows for larger potential payment 
shock than would normally be allowed on these loans to compensate 
for the lack of negative amortization provisions in this model.
---------------------------------------------------------------------------

(iv) The Present Value of Depreciation Write-offs for Multifamily 
Properties

    The value of depreciation write-offs to a new property owner is 
calculated with the present value formula used by Goldberg and Capone 
(1998): \268\
---------------------------------------------------------------------------

    \268\ The variable in the Goldberg and Capone (1998) article is 
called PVTAX, but it is the same as the DW variable shown here. 
Weights for  and  are the percent of taxpayers 
in adjusted gross income groups.
[GRAPHIC] [TIFF OMITTED] TP13AP99.046

    DWt is the present value of depreciation write-offs for 
each $100 of investment in rental housing, and can be thought of as the 
percentage of the investment tax basis that is returned to the investor 
through depreciation write-offs. The tax rate data used to calculate 
this variable are described above in section IV.D.2., Historical Data.
    In addition to tax rates, an estimate of a required rate of return 
is needed to calculate the present value of depreciation write-offs. 
For this OFHEO used an estimate of the weighted average cost of 
capital, with 20 percent equity and 80 percent debt financing. The cost 
of debt financing is measured with data from the Enterprises on the 
average coupon rate of multifamily fixed-rate mortgages in each year, 
1983-95 (rf,t). The cost of equity is calculated with data 
from the Enterprises and the Bureau of Labor Statistics. In particular, 
if property NOI is expected to increase annually at the rate g, then 
the cap rate, CAP, can be thought of as equaling the required return on 
equity (re) minus the growth rate, gt. This 
implies that the required return on equity equals:
[GRAPHIC] [TIFF OMITTED] TP13AP99.047

    CAP0,t is estimated using cap rate values for all 
Enterprise loans originated in year, t, and the relationships estimated 
in equation 27. Values for gt are three-year average growth 
rates of rents, using the Bureau of Labor Statistics CPI residential 
rent series, national average (for years t-2, t-1, and t).
    The weighted average discount rate for all loans in year, t, is 
then:

[[Page 18203]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.048


    Table 34 shows values of DWt in the study period, 1983-
95.
[GRAPHIC] [TIFF OMITTED] TP13AP99.222

(v) Program Restructuring

    The original cash purchase programs of the Enterprises were 
implemented in an overheated lending environment in which appraisal 
practices allowed for inflation adjustments to rents when calculating 
property value. Such adjustments resulted in understatements of 
LTV0 and overstatements of DCR0, leading to the 
purchase of loans with understated credit risk and, eventually, to 
severe credit losses. In addition to the overstatement of anticipated 
rents, original multifamily cash-purchase programs at the Enterprises 
had other significant weaknesses. For these reasons, on loans purchased 
under original cash programs (Fannie Mae, 1983-1987, Freddie Mac, 1983-
1991) the stress test accounts for increased risk in two ways. The 
first method is to adjust LTV0 and DCR0 on 
original cash program loans to extract the average inflation factors. 
Internal research at OFHEO has concluded that reasonable adjustment 
multipliers are 0.85 for DCR0 and 1.27 for LTV0.
    The second method used to account for increased default risk in 
original cash programs is to include a dummy variable (PR) in the 
default equation. This measures the behavioral difference of loans 
purchased prior to program restructuring (1 = original cash purchase 
loan).

(vi) Default Type

    For most loans acquired through negotiated transactions, the loan 
event used to estimate defaults is a 90-day delinquency, rather than a 
foreclosure. A different event was chosen for these loans because the 
seller/servicer typically has a contractual obligation to repurchase 
delinquent loans from security pools and resolve the default. As a 
result, the Enterprises' data do not reflect which of these loans were 
cured or renegotiated and which resulted in property loss events. These 
loans will have more observed ``defaults'' because they include cures 
and loan modifications as well as property loss events. To adjust for 
this discrepancy, two dummy variables are included in the negotiated 
purchase default equation: one to flag ARM loans under repurchase 
contracts (RA), and one to flag fixed-rate loans under repurchase 
contracts (RF).

(vii) Loan Age

    Default risk is greatest in the years just after loan origination. 
Apartment projects are then most vulnerable to economic shocks because 
DCRt may be low, LTVt may be high, and it may 
take several years to create a viable market niche for the property. 
However, a financially troubled project will not default immediately. 
First, valuable depreciation write-offs may be available in the early 
years to counterbalance negative property cash flow. Second, working-
capital reserves may forestall default. And third, the owner may 
``bleed the project'' by deferring maintenance and other expenditures 
prior to delinquency.\269\ Age denotes the loan year of an observation. 
Thus, if a loan was originated in 1985, its age is 1 in 1985, 2 in 
1986, and so on.
---------------------------------------------------------------------------

    \269\ This final reason is discussed by Quercia (1995) and by 
Riddiough and Thompson (1993).
---------------------------------------------------------------------------

    Other studies of commercial mortgage defaults confirm that defaults 
tend to rise in the first years after loan origination and then, once 
the weakest loans exit, the conditional default rate declines.\270\ 
Preliminary analysis of Enterprise data indicated that the peak

[[Page 18204]]

default period is about four years after loan origination. To capture 
this underlying trend, a quadratic age function is included in the 
default equations.
---------------------------------------------------------------------------

    \270\ See Snyderman (1994).
---------------------------------------------------------------------------

b. Prepayment Equations

    The explanatory variables chosen for the prepayment equations are 
designed to capture multiple refinancing incentives: exercising the 
``call'' option (normal refinance); rebalancing debt and equity in the 
property (cash-out refinance); risk aversity with respect to pending 
balloon expirations (early payoffs); and balloon payoffs. The overall 
model is separated into five equations in order to best capture the 
differing prepayment incentives by product and product-life stage. For 
ease of exposition, these five equations are referred to here as 
``models.''
    The first model is for fixed-rate loans in the initial yield 
maintenance period, when refinancing has no immediate value. Beyond the 
yield maintenance period, fully amortizing and balloon loans with fixed 
interest rates are analyzed separately in two additional models. This 
approach is used because, after yield maintenance ends, balloon loans 
prepay more quickly than self-amortizing loans, reflecting borrower 
uncertainty surrounding interest rate movements leading up to the time 
of loan maturity, when a payoff is required. At maturity, balloon loans 
are viewed as having payoffs rather than prepayments. The dynamics of 
required payoffs are much different from those of voluntary prepayments 
prior to maturity. Therefore, a fourth equation is estimated for 
balloons during and after the maturity year. This fourth model includes 
both fixed-and adjustable-rate balloons. The fifth and final model is 
for adjustable-rate mortgages other than those that may have reached a 
balloon maturity point. Adjustable rate mortgages do not have yield 
maintenance terms, and their refinancing incentives are different from 
those of fixed-rate mortgages.
    In prepayment model 4, for balloon payoffs, OFHEO recognizes that 
while there is a contractual obligation to find new sources of 
financing at the balloon point, those with weak financials may not 
qualify for new funding. The Enterprises, like all lenders, however, 
are often unwilling to initiate foreclosure if loan payments are being 
made under the current (but now expired) contract. OFHEO's approach to 
these extended loans is, therefore, to continue to model payoff rates 
at and beyond the balloon point.
    Table 35 sets forth the structure of the explanatory variables used 
in the five prepayment equation/models, as follows:

[[Page 18205]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.223



(i) Relative Spreads in Interest Rates

    The relative difference between coupon and market interest rates is 
the primary call option variable used in the prepayment equations. For 
fixed-rate loans (prepayment models 1-3), OFHEO includes spread 
variables when market rates are lower (RSDj,t) and when 
market rates are higher than coupon rates

[[Page 18206]]

(RSUj,t). Asymmetry of effects is allowed for because drops 
in rates affect refinancings with different motivations than rises in 
rates do. Rate declines stimulate refinancings designed to lower 
interest costs, while rate increases discourage cash-out refinancings.
[GRAPHIC] [TIFF OMITTED] TP13AP99.049

[GRAPHIC] [TIFF OMITTED] TP13AP99.050

[GRAPHIC] [TIFF OMITTED] TP13AP99.238

    The down-rate spread variable, RSDj,t, is given added 
weight in the years preceding balloon maturity (model 2) in order to 
capture the risk aversity of borrowers with respect to interest rate 
movements leading up the balloon point. This weight is added through 
two interactive variables. First, RSD1j,t, is 
RSDj,t multiplied by a 0/1 dummy variable that is turned on 
during the year immediately preceding the balloon year (13-24 months 
prior to the maturity month). The second, RSD2j,t, is 
RSDj,t multiplied by a 0/1 dummy variable that is turned on 
during the second year preceding the balloon year (months 25-36 prior 
to the maturity month).
    For adjustable rate mortgages (model 5), the spread variable is not 
separated into positive and negative components, but is allowed to have 
one effect for both increases and decreases in interest rates.\271\ 
Because ARM coupon rates change every year, the relative spread 
variable is used to capture the slope of the yield curve, which 
indicates whether it is more valuable to retain the ARM or to refinance 
into a fixed-rate loan.
---------------------------------------------------------------------------

    \271\ Also, a lack of observations on high interest rate 
environments made it difficult to estimate separate effects for rate 
rises (RSU).
[GRAPHIC] [TIFF OMITTED] TP13AP99.051

(ii) Market Interest Rate

    An additional interest rate variable is added to the ARM equation 
(model 5). This is the fixed-rate mortgage rate, rf,t, and 
it captures incentives to refinance into fixed-rate products when the 
level of rates is low.

(iii) Years-To-Go in the Yield Maintenance Period

    Yield maintenance fees are a function of the remaining time until 
the end of the prepayment restriction period. As the yield maintenance 
period draws to a close, the prepayment penalties decline and the value 
of refinancing increases. To capture this change, prepayment model 1 
has a variable that measures the years-to-go until the end of the yield 
maintenance period (YTGt).\272\
---------------------------------------------------------------------------

    \272\ OFHEO experimented with variables that attempted to 
capture the impact of yield maintenance fees on refinancing 
incentives, but the fixed effects (years-to-go) proved to be a 
better predictor of historical mortgage performance.
---------------------------------------------------------------------------

    A small number of older Enterprise loans had prepayment lockouts 
for a period of years, rather than financial prepayment fees. For these 
loans, we set YTGt equal to 10 (its maximum value) 
throughout the restriction period.

(iv) Loan-to-Value Ratio

    Investors in multifamily properties will engage in cash-out 
refinancings to increase returns on invested equity. This refinance 
motivation as LTV falls over time is captured by including 
LTVt as an explanatory variable.

(v) Loan Age

    The baseline prepayment hazard is a function of the desired holding 
period of investors. The holding period is heavily influenced by tax 
laws: accelerated writeoffs and shorter depreciation schedules 
encourage shorter holding periods. It is also affected by exogenous 
factors, e.g., investor retirement. Lacking data to measure the 
expected holding periods of investors, we assume that the distribution 
of expected holding periods, and their effect on baseline prepayment 
rates, can be captured through a quadratic function of mortgage 
age.\273\
---------------------------------------------------------------------------

    \273\ Follain, et al. (1997) attempt a fourth-order function of 
age to provide a more flexible baseline hazard function, but the 
third and fourth order terms are not statistically significant. 
Therefore, OFHEO accepts a second-order age function as sufficient 
for capturing the distribution of expected investor holding periods.

---------------------------------------------------------------------------

[[Page 18207]]

(vi) Probability of Qualifying To Refinance

    An important obstacle to call option exercise is qualifying for a 
new loan. Because information on property financials after loan 
origination is not available, it is not known which properties can, at 
any point in time, meet minimum standards, DCR=1.20 and LTV=0.80. 
Instead, the model uses the same approach employed for default 
analysis, calculating the joint probability that DCR and LTV will meet 
minimum qualification standards (PQt). PQt is 
measured by evaluating the bivariate normal distribution shown in 
equation 42 with new integration limits:
[GRAPHIC] [TIFF OMITTED] TP13AP99.052

where, for any given loan (j) in any given time period (t):
[GRAPHIC] [TIFF OMITTED] TP13AP99.053

[GRAPHIC] [TIFF OMITTED] TP13AP99.054

[GRAPHIC] [TIFF OMITTED] TP13AP99.239

    This effectively estimates the probability:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.055
    
(vii) Summary of Prepayment Models

    In summary, the five prepayment models (equations) are organized as 
follows:
1. Model 1: All Fixed-Rate Mortgages-Fully Amortizing and Balloon-in 
the Yield Maintenance Period
    Includes explanatory variables to capture investor holding horizons 
(AYt, AYt2), normal refinancings 
(RSDt), cash out refinancings (LTVt), adverse 
interest rate effects on cash-out refinancings (RSUt), and 
effects on normal refinancings due to yield maintenance 
(YTGt).
2. Model 2: Balloon Loans After Yield Maintenance, but Prior to the 
Maturity Year
    Includes explanatory variables for normal refinancings 
(RSDt), cash-out refinancings (LTVt), preballoon 
incentives to refinance and avoid the uncertainty of interest rates at 
maturity (RSD1t and RSD2t), and the various 
investment horizons of borrower/owners (AYt, 
AYt2). The variable for adverse interest rate 
offsets to cash-out refinancings (RSUt) is not included in 
this equation because of a lack of positive observations in the 
historical data series.\274\ The coefficient from model 3 is used for 
this variable in this equation in stress test application.
---------------------------------------------------------------------------

    \274\ Estimating the regression equation with both RSD and RSU 
does not significantly change the coefficient on RSD. The RSU 
coefficient is negligible and without statistical significance.
---------------------------------------------------------------------------

3. Model 3: Self-Amortizing Fixed-Rate Loans After Yield Maintenance
    Includes explanatory variables for investment horizons 
(AYt, AYt2), normal refinancings 
(RSDt), cash-out refinancings (LTVt), and adverse 
interest-rate effects on cash-out refinancings (RSUt).
4. Model 4: Balloon payoff
    Includes an explanatory variable for the ability of the property to 
qualify for new financing (PQt). This is the only variable 
because at the balloon point there are no longer prepayments, only 
payoffs.
5. Model 5: Prepayments of Adjustable Rate Mortgages
    Includes explanatory variables for the expected investment horizons 
of borrower/owners (AYt, AYt2), cash-
out refinance incentives (LTVt), and incentives to refinance 
out of ARMs and into fixed-rate products (RSt and 
rf,t).
5. Results of the Statistical Estimation of Default and Prepayment 
Equations
    Table 36 provides maximum likelihood estimates of coefficients in 
the two default equations.

[[Page 18208]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.224


    All coefficient signs are as expected in both default equations, 
and all variables have significant effects, both statistically and 
practically. The age patterns in each equation (including the constant 
term) are similar, but the joint probability (JPt) has a 
larger effect on negotiated purchase default rates than on cash-
purchase default rates. This finding may result from the fact that most 
negotiated loan defaults were 90-day delinquency rather than 
foreclosures, and delinquencies may be more sensitive to changes in 
variables, such as vacancy rates, that underlie JPt.
    The dummy variable for program restructuring (PR) has a coefficient 
of 0.6203. That implies that annual default rates on original cash-
purchase loans are roughly 1.6 times those of new-cash purchase 
loans.\275\ The value of the depreciation write-off coefficient 
indicates that the decrease in depreciation allowances that were part 
of the 1986 tax reform increased default rates roughly 40 percent.\276\
---------------------------------------------------------------------------

    \275\ The marginal probability of binary logit coefficients is 
P(1-P), where  is the coefficient and P is 
the probability estimated with the coefficient set to zero. So, if 
P=1 percent, then the increase in probability for original cash 
program loans is equal to 0.61 percent, and the original-program 
probability is 1.61 percent. If P=0.5 percent, then the probability 
for an original-program cash loan is 0.8 percent (marginal 
probability is 0.30 percent).
    \276\ This finding is explored in greater depth in Goldberg and 
Capone (1998).
---------------------------------------------------------------------------

    Table 37 provides maximum likelihood estimates of the five 
prepayment models (equations). All of the coefficient estimates have 
the expected signs and provide consistent results. While the 
coefficient of the negative spread variable (RSDt) is larger 
during the yield maintenance than it is out of yield maintenance, it 
actually has a much smaller effect on the probability of prepayment. In 
this functional form, the coefficient represents (approximately) the 
percentage change in prepayments per unit change in rates. Because 
prepayment rates are much greater for loans out of yield maintenance, 
the larger proportional effect for loans in yield maintenance is still 
much smaller in absolute terms.

[[Page 18209]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.225


    As expected, balloon loans in the post-yield maintenance period 
have higher refinance incentives than do fully-amortizing loans, and, 
therefore, there is a higher coefficient on RSDt in 
prepayment (model 2) than in prepayment (model 3), with even greater 
effects as balloon maturity approaches (RSD1t and 
RSD2t).
    Cash-out refinancings (LTVt), are much stronger in the 
post-yield maintenance period, than during yield maintenance, as 
expected. ARM loan prepayments (model 5) are sensitive to all of the 
factors in the model. The balloon payoff (model 4) shows that the 
probability of qualifying for a refinancing is a valuable predictor of 
annual payoff rates in the balloon and post-balloon years.

[[Page 18210]]

6. Application to the Stress Test
    The risk-based-capital stress test matches default and prepayment 
models for each loan group by loan characteristics and age. Because the 
stress test uses loan aggregates (groups), the probabilities that 
result from use of the statistical equations can be thought of as rates 
of default and prepayment on the outstanding balances in each loan 
group, in each month of the stress period. But the default and 
prepayment models generated here produce annual rates of default and 
prepayment. Monthly rates are derived by first calculating annual 
equivalent rates in each month, given the explanatory variable values 
in that month, and then converting the annual rates to their monthly 
equivalents.
    The stress tests selects the appropriate default equation used for 
each loan group based solely on the value of the Program Type data 
field in the Enterprises' loan characteristics data. The stress test 
chooses among prepayment equations based upon Product Type and loan 
Origination Term fields in the loan characteristics data, and also upon 
a computed mortgage age variable. Balloon loans use three separate 
prepayment models throughout loan life: in yield maintenance (model 1), 
post-yield maintenance (model 2), and payoff period (model 4). Fully 
amortizing ARMs will use just one equation (model 5), balloon ARMs will 
use two equations (model 5, and then model 4 at balloon term). Fully 
amortizing fixed-rate loans will use two prepayment equations, model 1 
during yield maintenance and model 3 afterward. The estimated default 
and prepayment equations are used not in binary logistic equations, but 
rather in trinomial equations, as shown in equations 20 and 21, above. 
Use of the trinomial or, more generally, multinomial probability 
equations assures that prepayments and defaults are treated as 
competing risks in stress test application.
    Use of the statistical equations in the stress test also involves 
some cross-equation grafting of coefficients. This is because the 
historical data on post-yield maintenance balloon loans (model 2) do 
not have sufficient observations where market interest rates are higher 
than coupon rates to compute a reliable coefficient for RSU. Instead, 
the coefficient for the variable RSUt in model 3 is added 
into model 2 so that the effect of the up-rate stress test can be 
captured. An additional cross-equation grafting is performed for the 
added balloon-year effect for the joint probability variable in the 
default equations (BJP). There are insufficient loans with balloon 
maturity in the negotiated purchase data set to estimate a coefficient. 
Therefore, the coefficient estimate from the cash purchase default 
equation is used in the negotiated purchase default equation in the 
stress test.
    The cap rate multiplier used to update property value from NOI 
(equation 27) is updated in the stress test using ten-year constant 
maturity Treasury yields, rather than mortgage coupon rates. Which 
interest rate is used to capture percent changes in interest rates is 
not important, and the ten-year constant maturity Treasury Yield series 
is the fundamental interest rate series used in the stress test. The 
stress test also uses a simplifying assumption for the depreciation 
writeoff variable, DWjt. Rather than predict the value of 
this variable into the future, OFHEO chose to use the 1995 value (9.27) 
for the entire stress period, in both up- and down-rate scenarios.
7. References
Abraham, Jesse (1993a). A Cash Flow Model of Property Performance, 
unpublished manuscript, Freddie Mac Corporation, McLean, Virginia, 
December.
Abraham, Jesse (1993b). Credit Risk in Commercial Real Estate Lending, 
unpublished manuscript, Freddie Mac Corporation, McLean, Virginia, 
December.
Abraham, Jesse M. and H. Scott Theobald. 1997. ``Commercial Mortgage 
Prepayments,'' in Frank J. Fabozzi and David P. Jacob, eds., The 
Handbook of Commercial Mortgage-Backed Securities. New Hope, PA: Frank 
J. Fabozzi Associates, 55-74.
Altman, Edward I. (1983). Corporate Financial Distress. New York: John 
Wiley & Sons, 1983.
Barnes, Walter C. and S. Michael Gilberto (1994). A Model for Assessing 
Commercial Mortgage Risk-Based Capital Factors, mimeo.
Begg, C.B. and R. Gray (1984). ``Calculation of Polychotomous Logistic 
Regression Parameters Using Individualized Regressions,'' Biometrica, 
71:11-18.
Boyer, Lawrence G., James R. Follain, Jan Ondrich, and Richard A. 
Piccirillo, Jr. 1997. A Hazard Model of Prepayment and Claim Rates for 
FHA Insured Multifamily Mortgages, unpublished paper. Arlington, VA: 
Price Waterhouse, December.
Brennan, M. and E. Schwartz (1985). Evaluation Natural Resource 
Investments, Journal of Business, 135-157.
Capone, Jr., Charles A. (1991). Bankruptcy, Survival, and the 
Multifamily Mortgage: A Methodological Primer for HUD Staff, 
unpublished manuscript, Washington, DC, U.S. Department of Housing and 
Urban Development, August.
Childs, Paul D., Steven H. Ott, and Timothy J. Riddiough. 1995. The 
Pricing of Multi-Class Commercial Mortgage-Backed Securities. 
Unpublished manuscript, MIT Center for Real Estate, February.
Danter, Kenneth F. (1996). ``Smart Investments in Multifamily,'' 
Mortgage Banking, July, 74-79.
DiPasquale, Denise and Jean L. Cummings (1992). ``Financing Multifamily 
Rental Housing: The Changing Role of Lenders and Investors,'' Housing 
Policy Debate 3 (1), 77-116.
Dyl, E.A. and H.W. Long (1969). Abandonment Value and Capital 
Budgeting: Comment, Journal of Finanace, 88-95.
Elmer, Peter J. and Anton E. Haidorfer. 1997. ``Prepayments of 
Multifamily Mortgage-Backed Securities.'' The Journal of Fixed Income 
(March), 50-62.
Follain, James R. and Jan Ondrich. 1997. ``Ruthless Prepayment? 
Evidence from Multifamily Mortgages,'' Journal of Urban Economics 41 
(January), 78-101.
Follain, James R., Jan Ondrich and Sinha P. Gyan (1990). A Hazard Model 
of Multifamily Mortgage Prepayments. Discussion Paper No. 54, 
Department of Economics, Syracuse University, December 1990.
Foster, Chet and Robert Van Order (1984). ``An Option Based Model of 
Mortgage Default,'' Housing Finance Review 3 (4), 351-372.
Goldberg, Lawrence (1994). Claims Forecasting Models for FHA 
Multifamily Housing Loans. Reston, Virginia: Economic Research 
Laboratory, Inc., under contract to the U.S. Department of the Treasury 
through HCI Inc., Reston, Virginia, August 26.
Goldberg, Lawrence and Charles A. Capone, Jr. 1997. Motivation and 
Testing of a Double-Trigger Hypothesis for Multifamily Loan Defaults. 
Unpublished manuscript, Office of Federal Housing Enterprise Oversight: 
Washington DC.
Goldberg, Larry, and Capone, Jr., Charles A. (1998). ``Multifamily 
Mortgage Credit Risk: Lessons from Recent History,'' Cityscape 4 (1), 
93-113.
ICF Incorporated (1991). Predicting Financial Distress In HUD 
Multifamily Projects. Fairfax, Virginia: ICF

[[Page 18211]]

Incorporated, under contract with the U.S. Department of Housing and 
Urban Development, April 30.
Joy, O.M. (1976). Abandonment Values and Abandonment Decisions: A 
Clarification, Journal of Finanace, 1225-1228.
Kahn, Charles M. (1991). The Economic Role of Foreclosure Rules, ORER 
Letter, Spring, 8-11.
Kau, James B., D.C. Keenan, W.J. Muller III and J.F. Epperson (1987). 
The Valuation and Securitization of Commercial and Multifamily 
Mortgages, Journal of Banking and Finance 11, 525-546.
Kau, James B., D.C. Keenan, W.J. Muller III and J.F. Epperson (1990). 
``Pricing Commercial Mortgages and Their Mortgage-Backed Securities,'' 
Journal of Real Estate Finance and Economics 3, 333-356.
Mahue, Michelle A. (1991). ``The Economic Role of Statutory 
Redemption,'' ORER Letter, Spring, 12-13.
McFadden, Daniel (1975). ``The Revealed Preferences of a Government 
Bureaucracy: Theory.'' Bell Journal (Autumn), 401-416.
National Task Force on Financing Affordable Housing (1992). From the 
Neighborhoods to the Capital Markets. Washington, DC: Allstate 
Insurance Company, June.
Pedone, Carla I. (1991). ``Estimating Mortgage Prepayments and Defaults 
in Older Federally Assisted Rental Housing and the Possible Costs of 
Preventing Them,'' Housing Policy Debate 2 (2), 245-288.
Quercia, Roberto (1995). On Developing a Model of Mortgage Default for 
Multifamily Rental Housing, unpublished manuscript. Washington, DC: the 
Urban Institute, October.
Riddiough, Timothy J. and H.E. Thompson (1993). ``Commercial Mortgage 
Pricing with Unobservable Borrower Default Costs,'' Journal of the 
American Real Estate and Urban Economics Association 21 (3), 265-292.
Riddiough, Timothy J. and S.B. Wyatt (1994a). ``Strategic Default, 
Workout and Commercial Mortgage Valuation,'' Journal of Real Estate 
Finance and Economics 9 (1), 5-22Riddiough, Timothy J. and S.B. Wyatt 
(1994b). ``Wimp or Tough Guy: Sequential Default Risk and Signaling 
with Mortgages,'' Journal of Real Estate Finance and Economics 9 (3), 
299-322.
Robicheck, A. and J.C. Van Horne (1967). Abandonment Value and Capital 
Budgeting, Journal of Finance, 577-590.
Sharkawy, M. Atef and Walter C. Barnes (1992). ``Cost, Value, and 
Hybrid-Based Underwriting Criteria,'' The Journal of Real Estate 
Research 7 (2, Spring), 169-185.
Snyderman, Mark P. (1994). ``Update on Commercial Mortgage Defaults,'' 
The Real Estate Finance Journal, Summer, 22-32.
Titman, S. and W. Torous (1989). ``Valuing Commercial Mortgages: An 
Empirical Investigation of the Contingent Claims Approach to Pricing 
Risky Debt,'' Journal of Finance 44, 345-373.
Standard & Poors (1993). Credit Week, March 8. (Issue devoted to 
Commercial Mortgage Securities)Vandell, Kerry (1992). ``Predicting 
Commercial Mortgage Foreclosure Experience,'' Journal of the Americal 
Real Estate and Urban Economics Association 20 (1), 55-88.
Vandell, Kerry, Walter Barnes, David Hartzell, Dennis Kraft and William 
Wendt (1993). ``Commercial Mortgage Defaults: Proportional Hazards 
Estimation Using Individual Loan Histories,'' Journal of the American 
Real Estate and Urban Economics Association 4 (21, Winter), 451-480.

E. Multifamily Loss Severity

1. Introduction
    Owing primarily to limited available data, OFHEO's approach to 
modeling multifamily loss severity rates for stress test application is 
simpler than approaches chosen for other elements of mortgage 
performance. The number of multifamily loans in Enterprise portfolios 
is a fraction of the number of single family loans. Therefore, the 
number of defaulted multifamily loans is relatively small. Further, 
only one Enterprise, Freddie Mac, has reliable historical records of 
multifamily loss severity rates. Until the mid-1990s, Fannie Mae's 
multifamily default resolutions were handled by the various field 
offices, and there were no standard protocols for tracking and 
maintaining data elements on a loan-by-loan basis. The result is that 
OFHEO analysis of Enterprise experience is exclusively focused on that 
of Freddie Mac.
    Even so, the Freddie Mac program provides sufficient data to 
understand the various components of loss severity rates. They 
represent the worst historical experience of the Enterprises, and some 
of the worst experience on record for industry-wide multifamily 
mortgage loss severities. The Freddie Mac data are not extensive enough 
to allow a multivariate statistical analysis. The analysis outlined 
here is univariate: each element is examined individually, without 
explanatory variables. The result is that OFHEO chose for its stress 
test to use simple averages of various components of multifamily loss 
severity.
    Section 2 of this supplementary material on multifamily loss 
severity gives an outline of the conceptual framework, the plan OFHEO 
used in approaching multifamily loss severity rates; section 3 provides 
a discussion of the source data; section 4 is a summary of the data 
analysis; and section 5 concludes with an examination of how the loss 
severity components are applied in the stress test.
2. Conceptual Framework
    Loss severity is the net cost of resolving a mortgage default. It 
is most typically measured as a percentage of the unpaid principal 
balance (UPB) at the time of default.\277\ OFHEO measures severity in 
this way and then applies any available credit enhancements against the 
loss to arrive at a net loss to the Enterprises. Credit enhancements 
are not discussed in this supplement. A description of how the stress 
test applies credit enhancements can be found in the Appendix to this 
regulation.
---------------------------------------------------------------------------

    \277\ All references to UPB in this part of the supplement 
indicate UPB at time of default.
---------------------------------------------------------------------------

    OFHEO's general approach is to model only those loss severity rates 
associated with full foreclosure events. The one exception is for 
programs where the default event of record is a 90-day delinquency. 
This exception will be discussed below, under Data Analysis. 
Foreclosure results in the Enterprise taking title to the property, 
managing and rehabilitating it, and then marketing and selling the 
property. OFHEO also models the timing of events and cost elements 
associated with foreclosure and property management. As with single 
family loss severity rates, OFHEO recognizes three time frames in 
capturing costs and revenues associated with mortgage foreclosure: the 
first four months of delinquency, the time from default to foreclosure 
completion (which includes the first four months), and time of property 
inventory (from foreclosure completion to property disposition).
    After analyzing Enterprise data, and reviewing available research 
on multifamily loss severity, OFHEO chose to use simple averages of 
Enterprise experience, by loss component, and not to perform 
multivariate statistical analysis. Component analysis permits the use 
of discounting techniques to create effective loss severity rates at 
the time of default (one month after last-

[[Page 18212]]

paid-installment). OFHEO found no basis in the existing literature for 
multivariate statistical analysis of multifamily loss severities.
    OFHEO identified seven studies of loss severity, each of which 
relies upon data from a broad range of commercial property types, and 
each of which defines and measures severity rates somewhat 
differently.\278\ These studies primarily provide simple averages of 
loan-level loss severity rates, though some do attempt some statistical 
analysis of severity rates. Curry, et al (1990) model loss severities 
as a function of the type of organization managing the foreclosed 
property (public or private). Haidorfer (1997) performs a multivariate 
statistical analysis that looks at the type of property sale process 
(open auction, sealed-bid auction, or broker sales). He finds that the 
type of selling process does not influence severity rates. A third 
study by Ciochetti and Riddiough (1998) models expected property 
recovery rates as a function of mortgage terms, and a list of property 
type and region dummies.\279\ They find no statistical significance of 
original LTV, debt coverage ratio (DCR), loan age, or the mortgage 
interest rate.
---------------------------------------------------------------------------

    \278\ The seven studies are: Curry, Blalock, and Cole (1990); 
Snyderman (1994); Fitch Investors Service (1996); Ciochetti (1997); 
Haidorfer (1997); Barnes, Gilberto and Peyton (1998); and Ciochetti 
and Riddiough (1998).
    \279\ The Ciochetti and Riddiough study looks at expected 
recoveries immediately following foreclosure, where property value 
is appraised value, and no property management or disposition costs 
are included in the calculations.
---------------------------------------------------------------------------

3. Sources of Data
    OFHEO obtained loss severity data on multifamily loans from both 
Enterprises, but only Freddie Mac maintained a complete historical data 
base of all relevant revenue and expense components that was useful for 
this analysis.\280\ The analysis of foreclosure loss severities is then 
limited to 705 multifamily loans purchased by Freddie Mac, that 
subsequently defaulted between 1987 and 1995 and ended in foreclosure. 
Over 83 percent of these loans defaulted between 1990 and 1993, in what 
is considered the worst period in modern history for the commercial 
mortgage market. These data are supplemented by Freddie Mac data on 
other default resolutions. These additional data are used for 
projecting potential losses on negotiated purchase loans for which 
seller/servicers must repurchase and resolve all 90-day delinquencies. 
Once delinquencies are resolved, the seller/servicers bill the 
Enterprise for the net costs.\281\ Fannie Mae has a large portfolio of 
sold loans with these repurchase provisions and has maintained data on 
the claims for losses submitted by the seller/servicers. However, many 
of the claim records are incomplete and OFHEO therefore, relied on 
information on Freddie Mac default resolutions, and on information from 
other available studies, to determine a loss rate to charge against 90-
day delinquencies. Freddie Mac provided OFHEO with information on the 
chargeoffs associated with 160 non-foreclosure resolutions that 
occurred from 1990 to 1995.
---------------------------------------------------------------------------

    \280\ Until the mid 1990s, Fannie Mae's foreclosed property 
inventory was managed by the individual field offices. There were no 
standard protocols for recording or retaining expense and revenue 
components of loss severity on a loan-by-loan basis. Fannie Mae 
could only provide OFHEO with consistent data on event times 
(foreclosure and property disposition).
    \281\ When these loans are purchased by the Enterprises, the 
seller/servicers must establish resource accounts. These credit 
enhancements drawn on as first-lost protection before the 
Enterprises actually incur any costs from loan defaults in these 
mortgage pools.
---------------------------------------------------------------------------

    These data represent the worst historical experience of the 
Enterprises, which began purchasing conventional multifamily mortgages 
in 1983.\282\ The Freddie Mac data is among the largest and richest 
sets of information available to any researchers who have studied 
multifamily loss severities.
---------------------------------------------------------------------------

    \282\ Goldberg and Capone (1997) detail the problems that led to 
high default rates among multifamily mortgages in the late 1980s and 
early 1990s. These same factors led to high severity rates. In 
addition to market factors, Freddie Mac attributes its particularly 
bad performance to fraud by lenders that underwrote loans that were 
not of investment quality. An analysis of data shown in Investor 
Analyst Reports shows that in 1991, Freddie Mac's chargeoff for bad 
multifamily loans was more than its total chargeoff for bad single 
family loans, even though its multifamily portfolio of $10 billion 
was only three percent as large as the single family portfolio. This 
high rate of chargeoffs lasted from 1989 through 1992.
---------------------------------------------------------------------------

4. Data Analysis

a. Foreclosure Severity Rates

    Table 38 provides average values for loss severity components in 
the Freddie Mac foreclosure database. The cost components are each 
measured as a percent of the UPB at the time of default. These average 
rates are also computed using UPB as a weighting factor on each loan. 
This weighting provides a more accurate measure of portfolio severity 
rates than would a simple average.\283\ The operating loss per month is 
the difference between monthly property income (rents) and expenses, 
where expenses include property repairs. It is not surprising that this 
element is a net cost rather than a net revenue because defaulting 
properties will have high vacancy rates and significant needs for 
repairs. The net proceeds of property sale is arrived at by subtracting 
selling expenses and other prorated expenses (taxes and rents) due at 
settlement from the actual sales price of each property. The two time 
dimensions reported here are important for discounting the associated 
cash flows to arrive at an effective loss severity rate at time of 
default (one month after last-paid-installment). One cost element not 
shown in Table 38 is the interest passthroughs to security holders 
during the initial months of delinquency. In general, loans are 
repurchased from security pools by the 120th day of delinquency, so 
that four months of passthrough interest must be added to severity 
calculations in stress test application.
---------------------------------------------------------------------------

    \283\ UPB weighting is also used in the OFHEO single family loss 
severity analysis.

[[Page 18213]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.226


    Adding the cost components here produces a 54 percent loss 
severity. This sum is comparable to what is reported by Fitch (1996) in 
its study of commercial mortgage foreclosures. Fitch reports a 56 
percent average loss severity rate on foreclosures.\284\ The Fitch 
study had an (undefined) interest passthrough component. If added to 
the Freddie Mac severity components, a four-month passthrough at eight 
percent interest would increase their sum from 54 percent to roughly 58 
percent.
---------------------------------------------------------------------------

    \284\ It is not clear exactly how many foreclosures there are in 
the Fitch data set. Fitch reports 547 costly default resolutions of 
60-day delinquencies, of which it appears from other data given in 
the report (loss severity rates on foreclosure and non-foreclosure 
resolutions) that 147 are foreclosure events.
---------------------------------------------------------------------------

b. 90-Day Delinquency Severities

    Deriving a loss rate to use for 90-day delinquency events involves 
making inferences on the rate of foreclosure and other costly 
resolutions versus non-costly resolutions. Snyderman (1994) found that 
46 percent of 90-day delinquencies in life insurance company 
portfolios, 1972-1986, ended in foreclosure. Freddie Mac data are 
consistent with this finding. Freddie Mac data indicate that 
foreclosures plus other costly resolutions are 56 percent of total 90-
day delinquencies. Using 56 percent as the rate of costly loan 
resolutions, and applying a 70 percent foreclosure loss severity to 
them, produces a severity rate on 90-day delinquencies of just over 39 
percent.\285\
---------------------------------------------------------------------------

    \285\ The 70 percent loss rate on foreclosures comes from the 54 
to 58 percent reported earlier, with asset holding costs added.
---------------------------------------------------------------------------

5. Application to the Stress Test
    The loss severity components just described enter the stress test 
as cash flows at various points in the default time frame. These cash 
flows are discounted by a cost-of-debt interest rate to produce a net-
present-value loss severity rate in the month of default. The use of 
discounting provides an implicit funding cost. It reduces the value of 
final proceeds by an amount equal to the cost of funding the non-
performing assets (first the loan, and then the property), and it 
reduces the value of various expenditures to reflect the fact that cash 
is not actually expended in the month of loan default but could be 
invested at some rate-of-return for a number of additional months.What 
discounting does not include is the cost of funding that portion of the 
loan balance that is not recovered in the sale of the foreclosed 
property. That portion of funding cost is captured elsewhere in the 
stress test by ongoing interest expenses on debt that is in excess of 
what can be retired by the property sale proceeds.\286\ The ongoing 
interest expenses are captured in other parts of the stress test beyond 
the loss severity calculations.
---------------------------------------------------------------------------

    \286\ For retained loans, the debt supporting the mortgage UPB 
will already be on the Enterprise balance sheets at the time of 
default. For sold loans, however, asset funding occurs when the 
Enterprise buys the defaulting loan out of its security pool.
---------------------------------------------------------------------------

a. Foreclosure Loss Severity Rate Application

    The basic loss severity equation for foreclosure costs has five 
elements, as shown in this equation:
[GRAPHIC] [TIFF OMITTED] TP13AP99.056


[[Page 18214]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.240


    The first loss element is the UPB of the defaulted loan. It is set 
here equal to `1' or 100 percent. For sold loans, it is discounted for 
four months, which represents the timing of repurchasing the loan from 
the security pool. For retained loans, the UPB is not discounted 
because the economic loss occurs at the time of default. The second 
loss element is the passthrough interest expense for four months. This 
expense is discounted for two months as an approximation to discounting 
each month's pass through individually. This element only appears for 
sold loans.
    The third element of loss severity is the expense incurred to 
obtain a foreclosure judgment on the property. This cost includes all 
legal expenses for foreclosure and, when necessary, to release a 
bankruptcy stay, and other charges that may be incurred to obtain clean 
title to the property (e.g., property taxes due). The fourth element is 
the cost of operating and maintaining the foreclosured property while 
it is REO. And the fifth element is the net proceeds at final property 
disposition.
    The formula can be applied very simply. Using the cost elements in 
Table 38, along with a discount rate, r d,t = .06, and a 
passthrough rate, r p = .08:
[GRAPHIC] [TIFF OMITTED] TP13AP99.057

This reduces to 0.622 for sold loans and 0.615 for retained loans. If 
we increase the discount rate to 12 percent, the results change to 
0.661 for sold loans and 0.673 for retained loans. If the discount rate 
were reduced to three percent, the net present value severity rates 
would be 0.598 for sold loans and 0.581 for retained loans.

b. 90-Day Delinquencies

    For negotiated purchase loans with seller/servicer repurchase 
provisions, the stress test discounts to reflect a time lag between the 
initial delinquency and the claim payment. In the stress test, seller/
servicer claims on 90-day delinquencies are settled 12 months after 
default. Starting with the 39 percent severity rate for foreclosure 
alternatives reported above, and discounting for one year, yields a 
rate of around 34 to 37 percent, depending on the actual discount rate.
6. References
Barnes, Walter C., Gilberto, Michael, and Peyton, Martha S. (1997). 
Commercial Mortgage Loss Severity: What is it and How Should it be 
Measured? unpublished manuscript, Mortgage Analytics, West Hartford, 
CT.
Ciochetti, Brian A. (1997). Loss Characteristics of Commercial Mortgage 
Foreclosures, Real Estate Finance (Spring), 53-69.
Ciochetti, Brian A. and Riddiough, Timothy J.(1997). Foreclosure Loss 
and the Foreclosure Process: An Examination of Commercial Mortgage 
Performance, unpublished manuscript, University of North Carolina, 
Chapel Hill, Department of Finance.
Curry, Timothy, Blalock, Joseph, and Cole, Rebel (1990). Recoveries on 
Distressed Real Estate and the Relative Efficiency of Public Versus 
Private Management, AREUEA Journal 19 (4), 495-515.
Fitch Investors Service (1996). Trends in Commercial Mortgage Default 
Rates and Loss Severity. New York: Fitch Investors Service, Structured 
Finance Special Report, November 11.
Goldberg, Larry, and Capone, Jr., Charles A. (1998). Multifamily 
Mortgage Credit Risk: Lessons from Recent History, Cityscape 4 (1), 93-
113.
Haidorfer, Anton E. (1997). Relative Gross Recovery Rates on the Sale 
of Distressed Real Estate Owned Evidence from the Resolution Trust 
Corporation (RTC), unpublished manuscript, Mortgage Bankers Association 
of America, May.
Snyderman, Mark P. (1994). Update on Commercial Mortgage Defaults, The 
Real Estate Finance Journal, Summer, 22-32.

F. Property Valuation

1. Introduction
    The stress test simulates mortgage performance under housing market

[[Page 18215]]

conditions that reflect stresses comparable to those of the time and 
place of the benchmark loss experience (BLE). This section describes 
the data used to define and create variables that comprise the housing 
market conditions of the stress test.
    Three housing market condition variables are used in the stress 
test: house price growth rates, rent growth rates, and rental vacancy 
rates. House price growth rates are used to project single family 
mortgage performance, both default/prepayment rates and loss severity 
rates. Rent growth rates and vacancy rates are used to project 
multifamily default and prepayment rates.
    Section 2 of this part of the Technical Supplement describes the 
conceptual framework OFHEO used to determine the housing market 
condition variables in the stress test. Section 3 lists the sources of 
data used to develop these variables. Section 4 then describes the 
statistical analysis performed to transform source data into housing 
market condition variables.
2. Conceptual Framework
    The BLE is based upon the performance of 30-year, fixed-rate single 
family mortgages in four States--Arkansas, Louisiana, Mississippi, and 
Oklahoma--originated in 1983 and 1984, during the ten years following 
origination, as defined in the first NPR. The actual BLE covered twelve 
calendar years because benchmark loans could originate any time between 
January 1983 and December 1984, and the ten-year experience of the last 
loans originated during the benchmark time period lasted through 
December of 1994. For house prices, rent growth rates, and vacancy 
rates in the stress test, OFHEO defined the BLE as the years 1984 
through 1993--the middle ten years of the twelve-year period marking 
the BLE. OFHEO then identified sources of data that reflect the housing 
market conditions of the benchmark time and place, and that are 
compatible with historical data used to estimate statistical 
(econometric) models of mortgage default, prepayment, and loss 
severity.

a. Single Family House Price Appreciation Rates

    OFHEO sought publicly available data with geographic coverage that 
reflect stresses similar to those of the BLE. For house price growth 
rates, the stress test uses OFHEO HPI data from the West South Central 
(WSC) Census Division. Because the 1984-1993 WSC HPI series was used to 
calibrate the single family default- and severity-rate equations to the 
actual four-State benchmark loan performance,\287\ the same series also 
was used to define housing market conditions in the stress test. The 
WSC Census Division is similar geographically to the actual four-State 
BLE. The difference is that the WSC includes Texas, but not 
Mississippi. For the ten-year period, 1984-1993, the cumulative house 
price appreciation rate for the WSC Census Division is very similar to 
that of the four-State benchmark region. For the stress test, the OFHEO 
HPI is converted from index form into quarterly appreciation rates.
---------------------------------------------------------------------------

    \287\ Benchmark loss experience calibration is discussed in both 
the Single Family Default/Prepayment and the Single Family Severity 
sections of this Technical Supplement.
---------------------------------------------------------------------------

b. Vacancy Rates and Rent Growth Rates

    Rental market data--vacancy rates and rent growth rates--used in 
the statistical analysis of historical multifamily default and 
prepayment rates are also from government sources. Rent growth rates 
are from the residential rent component of the consumer price index 
(CPI), produced by the Bureau of Labor Statistics. Vacancy rates are 
from the rental vacancy rate series (H-111) produced by the Bureau of 
the Census. However, these data series are not used directly to reflect 
multifamily housing market conditions during the stress period because 
the available geographic aggregations and time periods do not closely 
match the four-State benchmark. The CPI residential rent index is not 
available for the appropriate geographic areas, and the H-111 state 
vacancy rate series is not available for 1984 and 1985.\288\
---------------------------------------------------------------------------

    \288\ The residential rent series includes MSA level data for 
New Orleans, beginning in 1986. The New Orleans data alone, however, 
were insufficient for use in representing the BLE.
---------------------------------------------------------------------------

    In light of these shortcomings, OFHEO identified a non-government 
source of data published by the Institute for Real Estate Management 
(IREM). However, the IREM data do not represent the same properties as 
the government data. IREM surveys include only apartments, while the 
government surveys (both rents and vacancies), include apartments and 
single family rental units. To assure consistency with the government 
series, statistical regression equations were estimated to use in 
adjusting the IREM data. The adjusted data can be thought of as 
answering the question, ``What would CPI and H-111 data look like if 
they were available in the benchmark area?'' The statistical 
regressions (detailed in section 4, Statistical Analysis) use data from 
all metropolitan statistical areas (MSAs) for which both IREM and CPI 
or H-111 data are available, to estimate statistically valid 
relationships. These equations are then applied to IREM data from the 
four-State area to assure that variables used in the stress test are 
compatible with the variables used to develop the statistical models.
3. Data Sources
    The sources of data used to develop the housing market condition 
variables for stress test application are as follows:
     OFHEO HPI Report, 1996:3, West South Central Census 
Division Series, 1983:4-1993:4.
     Bureau of Labor Statistics, Consumer Price Index, 
Residential Rent Component, MSA series, 1970-1995, annual index values.
     Bureau of the Census, H-111 Housing Vacancy Survey, rental 
unit vacancies, MSA series, 1981-1995, annual average vacancy rates.
     Institute for Real Estate Management. Conventional 
Apartments. Chicago, IL: IREM. Annual publications, 1981-1995, MSA 
level (median) dollar rents per square foot, (median) dollar vacancy 
losses per square foot, and number of apartments in survey.
4. Statistical Analysis

a. House Prices Appreciation Rates

    The use of the OFHEO HPI in the stress test requires no statistical 
analysis. Monthly house price appreciation rates are derived from the 
OFHEO HPI index in three steps. First, monthly appreciation rate 
indexes are created for each quarter by dividing that quarter's index 
value by the index value for the preceding quarter. Second, the 
logarithm of this new index is used as the growth rate factor for that 
quarter. Finally, the quarterly rate is divided by three to produce at 
monthly growth rate factors for each month in the quarter. In this 
manner, the 120 months of stress test HPI growth rate factors 
(gq,t) are produced from the 41 quarterly HPI values 
(HPIq), 1983:4-1993:4:

[[Page 18216]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.058


[GRAPHIC] [TIFF OMITTED] TP13AP99.241

    The gq,t are called growth rate ``factors'' because they 
are the continuous growth rate equivalents to actual, discrete growth 
as measured across each month and quarter.\289\ Stress test 
applications convert these factors to actual appreciation rates. This 
baseline series of monthly growth rates applies in both the up- and 
down-rate scenarios, but may be adjusted for inflation in the up-rate 
scenario.
---------------------------------------------------------------------------

    \289\ Continuous growth rates refer to a process whereby house 
price appreciation is a continuous process, throughout each month or 
quarter. The actual house price index that shows total appreciation 
across a month or quarter is just the exponential of the growth rate 
factor for that time period.
---------------------------------------------------------------------------

b. Rent Growth Rates

    The statistical analysis underlying the rent growth rate variable 
used in the stress test uses MSA level data from both IREM and the CPI 
for the 26 cities for which the CPI residential rent index is 
available.\290\ Annual growth rates for 1970-1995 were computed from 
both the IREM and CPI rent data, and the following pooled, time series, 
cross-sectional, weighted least squares regression was estimated:
---------------------------------------------------------------------------

    \290\ Statistical analysis was based upon what the Bureau of 
Labor Statistics calls its ``old series.'' The new series covers 29 
MSAs.
[GRAPHIC] [TIFF OMITTED] TP13AP99.059

[GRAPHIC] [TIFF OMITTED] TP13AP99.242

    The regression was weighted by the number of apartments that IREM 
surveyed in each MSA. The coefficient for IRj,y is 
significant at the 99 percent confidence level.
    IREM data are available for one city in each of the four benchmark 
States--Jackson, Little Rock, New Orleans, and Oklahoma City. A 
benchmark region rent growth rate series was computed from equation 57, 
using a simple average of annual IREM rent growth rates in each of 
these cities (1984-1993) to populate IRj,y. Monthly rent 
growth rates were then computed using the following compounding 
formula.
[GRAPHIC] [TIFF OMITTED] TP13AP99.060

[GRAPHIC] [TIFF OMITTED] TP13AP99.243

    Equation 58 produces final rent growth rates in discrete form, 
rather than continuous form, because the process used to create the 
original series was discrete. As with the house price growth rate 
factors, inflation adjustments may be applied in the up-rate scenario.

c. Vacancy Rates

    Because Census vacancy rate data are available at the State level 
starting in 1986, OFHEO uses the average of rates

[[Page 18217]]

in the four benchmark States, from 1986-1993 for the latter eight years 
of the stress test. For the first two years, OFHEO employs a 
statistical analysis similar to that for rent growth rates to create 
government-equivalent vacancy rates for 1984 and 1985, the first two 
years needed for the stress test. The weighted-least-squares regression 
matches MSA-level Census vacancy rates to IREM vacancy rates in the 
same cities. Matching data is available for 51 MSAs; 23 with Census 
data that begin in 1981, and another 28 for which Census data become 
available in 1986. The pooled cross-section, time series regression is:
[GRAPHIC] [TIFF OMITTED] TP13AP99.061

[GRAPHIC] [TIFF OMITTED] TP13AP99.244

    The coefficient on IVj,y is statistically significant at 
the 99 percent level, but the constant term is not statistically 
significant. This lack of significance is not surprising, given that 
the regression is relating rates of change and not levels of vacancy 
rates. In application, the constant term is dropped from the equation.
    To compute vacancy rates for 1984 and 1985, equation 59 is applied 
using average IREM vacancy rates for the four benchmark cities to 
compute rates of change for the four-State average Census vacancy rate. 
The resulting rate of change from 1986 to 1985 is first applied to the 
four-State average Census vacancy rate for 1986 to compute a 
government-equivalent vacancy rate for 1985. The procedure is repeated 
to compute the vacancy value for 1984. Finally, each annual vacancy 
rate in the ten-year series is applied to each month in the year to 
extend the series to cover the 120 months of the stress period.

V. Regulatory Impact

A. Executive Order 12612, Federalism

    Executive Order 12612 requires that Executive departments and 
agencies identify regulatory actions that have significant Federalism 
implications. ``Federalism implications'' is defined as regulations or 
actions that have substantial direct effects on the States, on the 
relationship or distribution of power between the national government 
and the States, or on the distribution of power and responsibilities 
between the Federal and State government. This proposed regulation has 
no Federalism implications that warrant the preparation of a Federalism 
Assessment in accordance with Executive Order 12612.

B. Executive Order 12866, Regulatory Planning and Review

    This regulation has been reviewed by the Office of Management and 
Budget (OMB) in accordance with Executive Order 12866. OMB has 
determined that this is an economically significant rule. Included in 
the preamble to the proposed rule is an economic analysis of the 
proposal's impact on the regulated entities, and in particular on 
mortgage credit, of various alternatives. It contains a technical 
supplement providing detail on the specifications and estimations of 
econometric models for mortgage performance, and how those statistical 
models are applied in the proposed risk-based capital stress test.
    The proposed regulation implements the 1992 Act's requirement that 
OFHEO establish a risk-based capital requirement for the Enterprises. 
Along with the existing minimum capital leverage ratios and the 
examination function, the stress test is designed to ensure that the 
Enterprises have adequate capital and operate in a safe and sound 
manner.
    It is difficult to estimate precisely the particular benefits and 
costs associated with the risk-based capital requirement. Where 
possible, section II. C., Implications of the Proposed Rule discusses 
and quantifies the potential benefits and potential costs in more 
detail. Otherwise, that section characterizes the benefits and costs 
qualitatively. The analysis indicates that the anticipated benefits 
from implementing the risk-based capital regulation outweigh the 
anticipated costs. It further indicates that the proposed regulation 
ensures that risk is held at an appropriate level, while imposing the 
least burden on the Enterprises.
    By carrying out Congress' intent to implement the risk-based 
capital requirement, OFHEO would reduce the potential for Enterprise 
insolvency by protecting against interest rate, credit, and management 
and operations risk. By ensuring their safety and soundness, the 
regulation allows the Enterprises to continue to carry out their public 
purposes.\291\ These include providing stability in the secondary 
market for residential mortgages and providing access to mortgage 
credit in central cities, rural areas, and underserved areas. In 
addition, the regulation will also ensure that the Enterprises will 
continue to provide benefits to the primary mortgage market such as 
standardizing business practices.\292\
---------------------------------------------------------------------------

    \291\ 1992 Act, section 1302(2) (12 U.S.C. 4501(2)).
    \292\ Managing Risk in Housing Finance Markets: Perspectives 
from the Experiences of the United States of America and Mexico, 
OFHEO and the Mortgage Bankers Association of America (June 11, 
1998).
---------------------------------------------------------------------------

    Other benefits of the risk-based capital requirement are (1) making 
the Enterprises' capital requirement more sensitive to differences in 
risk exposures, (2) discouraging the Enterprises from taking excessive 
risks by making riskier behavior more costly, and (3) ensuring that the 
Enterprises maintain adequate capital in stressful credit and interest 
rate environments. Implementing a risk-based capital requirement with 
credit risk and interest rate risk components will help ensure that the 
Enterprises' capital requirement is more closely related to the risks 
that they incur. Adopting the proposed rule will result in a capital 
requirement that corresponds more closely to capital levels that the 
marketplace would demand in the absence of the benefits afforded by the 
government sponsorship of the Enterprises, and will lead to gains in 
overall economic efficiency.

[[Page 18218]]

Moreover, by evaluating risk in a forward-looking, dynamic manner, the 
stress test identifies potential problems before they become 
significant.
    As detailed in the Implications section, the Proposed Rule may 
impose some costs on the Enterprises. Nevertheless, any such costs are 
the necessary and reasonable costs of carrying out Congress' intent 
that the Enterprises remain financially solvent, which will enable them 
to out their important public purposes.
    Changes to comply with the risk-based capital requirement can be 
accomplished at relatively low costs. Both Enterprises can employ 
various practices and procedures to manage credit risk and interest 
rate risk by adjusting their holdings or operations. For example, one 
method to reduce credit risk exposure is to increase use of credit 
enhancements with highly-rated counterparties. One method to reduce 
interest risk exposure is to purchase derivative contracts.
    By complying with an effective risk-based capital requirement, the 
Proposed rule may in fact reduce Enterprise costs by enhancing investor 
confidence. This is consistent with a study by Standard & Poor's (S&P) 
that provided risk-to-the-government credit ratings for the 
Enterprises.\293\ While S&P had rated Fannie Mae A- and Freddie Mac A+ 
in 1991, the 1997 report upgraded the ratings of both Enterprises to 
AA-. S&P cited increased governmental oversight by OFHEO as an 
important factor in these higher ratings. It further noted that 
``OFHEO's regulatory oversight [of Freddie Mac] also gives comfort that 
appropriate interest rate risk mitigation steps would be taken as 
needed.'' \294\
---------------------------------------------------------------------------

    \293\ Final Report of Standard & Poors to OFHEO, Contract No. 
HE09602C (February 3, 1997).
    \294\ Contract No. HE09602C, p. 10.
---------------------------------------------------------------------------

C. Executive Order 12988, Civil Justice Reform

    Executive Order 12988 sets forth guidelines to promote the just and 
efficient resolution of civil claims and to reduce the risk of 
litigation to the government. The proposed regulation meets the 
applicable standards of sections 3(a) and (b) of Executive Order 12988.

D. Regulatory Flexibility Act

    The Regulatory Flexibility Act (5 U.S.C. 601 et seq.) requires that 
a proposed regulation that has a significant economic impact on a 
substantial number of small entities must include an initial regulatory 
flexibility analysis describing the rule's impact on small entities. 
Such an analysis need not be undertaken if the agency head certifies 
that the rule will not have a significant economic impact on a 
substantial number of small entities. 5 U.S.C. 605(b).
    OFHEO has considered the impacts of the proposed risk-based capital 
regulation under the Regulatory Flexibility Act. The proposed 
regulation does not have a significant effect on a substantial number 
of small entities.
    This proposed regulation would not have a significant economic 
impact on a substantial number of small entities since it is applicable 
only to the Enterprises, which are not small entities for purposes of 
the Regulatory Flexibility Act. Therefore, the General Counsel of OFHEO 
acting under delegated authority has certified that the proposed 
regulation would not have a significant economic impact on a 
substantial number of small entities.

E. Paperwork Reduction Act

    The Paperwork Reduction Act of 1995, 44 U.S.C. Chapter 35 requires 
that regulations involving the collection of information receive 
clearance from the Office of Management and Budget (OMB). The risk-
based capital proposal contains no such collection of information 
requiring OMB approval under the Paperwork Reduction Act.

List of Subjects in 12 CFR Part 1750

    Capital classification, Mortgages, Risk-based capital.

    Accordingly, for reasons set forth in the preamble, the Office of 
Federal Housing Enterprise Oversight proposes to amend 12 CFR part 1750 
as follows:

PART 1750--CAPITAL

    1. The authority citation for part 1750 as published at 61 FR 
29619, June 11, 1996, continues to read as follows:

    Authority: 12 U.S.C. 4513, 4514, 4611, 4612, 4614, 4618.


Sec. 1750.5  [Removed]

    2. Remove Sec. 1750.5.
    3. Amend Sec. 1750.12 of part 1750 as published at 61 FR 29620, 
June 11, 1996, by revising paragraph (a) to read as follows:


Sec. 1750.12  Procedures and Timing.

    (a) Each Enterprise shall file with the Director a risk-based 
capital report each quarter, or at such other times as the Director 
requires. The report shall contain information identified by OFHEO in 
written instructions to each Enterprise.
* * * * *
    4. Revise the Appendix to subpart B of part 1750 as published at 61 
FR 29621, June 11, 1996, to read as follows:

Appendix to Subpart B of Part 1750--Risk-Based Capital Test 
Methodology and Specifications

1.0  Identification of the Benchmark Loss Experience
    1.1  Definitions
    1.2  Data
    1.3  Procedures
2.0  Identification of a New Benchmark Loss Experience
3.0  Computation of Risk-Based Capital Level
    3.1  Enterprise Data
    3.1.1  Overview
    3.1.2  Whole Loans
    3.1.2.1  Characteristics Used to Create Loan Groups
    3.1.2.2  Loan Group Characteristics
    3.1.2.3  Individual Loan Data
    3.1.2.4  Single Family Mortgage Portfolio-Wide Information
    3.1.3  Mortgage-Related Securities
    3.1.3.1  Single Class MBS Issued by the Enterprises and Ginnie 
Mae
    3.1.3.2  Derivative Mortgage Securities Issued by the 
Enterprises and Ginnie Mae
    3.1.3.3   Mortgage Revenue Bonds and Miscellaneous Mortgage-
Related Securities
    3.1.4  Non-Mortgage Financial Instruments
    3.1.5   Operations, Taxes, and Accounting
    3.1.5.1  Data Required to Calculate Taxes, Operating Expenses, 
and Dividends
    3.1.5.2  Balance Sheet as of the Start of the Stress Test
    3.1.6  Other Off-Balance-Sheet Guarantees
    3.2  Commitments
    3.2.1  Overview
    3.2.2  Inputs
    3.2.2.1  Loan data
    3.2.2.2  Interest Rate Data
    3.2.3  Procedures
    3.2.4  Output
    3.3  Interest Rates
    3.3.1  Overview
    3.3.2  Inputs
    3.3.3  Procedures
    3.3.3.1  Identify Starting Values
    3.3.3.2  Project the Ten-Year CMT
    3.3.3.3  Project the Ten Other CMTs
    3.3.3.4  Project Non-Treasury Interest Rates
    3.3.3.5  Project Borrowing Rates
    3.3.4  Output
    3.4  Property Valuation
    3.4.1  Overview
    3.4.2  Inputs
    3.4.3  Procedures
    3.4.4  Output
    3.5  Mortgage Performance
    3.5.1  General
    3.5.2  Single Family Default and Prepayment
    3.5.2.1  Overview
    3.5.2.2  Inputs
    3.5.2.3  Procedures
    3.5.2.4  Output
    3.5.3  Single Family Loss Severity
    3.5.3.1  Overview
    3.5.3.2  Inputs
    3.5.3.3  Procedures
    3.5.3.4  Output
    3.5.4  Multifamily Default and Prepayment

[[Page 18219]]

    3.5.4.1  Overview
    3.5.4.2  Inputs
    3.5.4.3  Procedures
    3.5.4.4  Output
    3.5.5  Multifamily Loss Severity
    3.5.5.1  Overview
    3.5.5.2  Inputs
    3.5.5.3  Procedures
    3.5.5.4  Output
    3.6  Other Credit Factors
    3.6.1  Overview
    3.6.2  Input
    3.6.3  Procedures
    3.6.3.1  Identifying Other Credit Factors
    3.6.3.2  Classifying Rating Categories in the Stress Test
    3.6.3.3  Accounting for Other Credit Factors
    3.6.4  Output
    3.7  Mortgage Credit Enhancements
    3.7.1  Overview
    3.7.2  Inputs
    3.7.2.1  Enterprise Data on Mortgage Credit Enhancements
    3.7.2.2  Public Rating Information
    3.7.2.3  Counterparty Coverage Reduction Information
    3.7.3  Procedures
    3.7.3.1  Classification of Credit Enhancements
    3.7.3.2  Calculating Percentage Coverage and Dollar Coverage 
Amounts:
    3.7.3.3  Calculating Percent of UPB Covered by Each Counterparty 
Rating Category
    3.7.3.4  Calculating the Percent of UPB Under Dollar-Denominated 
Coverage
    3.7.3.5  Calculating Coverage Against Credit Losses
    3.7.4  Output
    3.8  Other Off-Balance Sheet Guarantees
    3.8.1  Overview
    3.8.2  Input
    3.8.3  Procedures
    3.8.4  Output
    3.9  Cash Flows
    3.9.1  Whole Loans
    3.9.1.1  Overview
    3.9.1.2  Inputs
    3.9.1.3  Procedures
    3.9.1.4  Output
    3.9.2  Mortgage-Related Securities
    3.9.2.1  Overview
    3.9.2.2  Inputs
    3.9.2.3  Procedures
    3.9.2.4  Outputs
    3.9.3  Debt and Related Cash Flows
    3.9.3.1  Overview
    3.9.3.2  Inputs
    3.9.3.3  Procedures
    3.9.3.4  Output
    3.9.4  Non-Mortgage Investment and Investment-Linked Derivative 
Contract Cash Flows
    3.9.4.1  Overview
    3.9.4.2  Inputs
    3.9.4.3  Procedures
    3.9.4.4  Output
    3.10  Operations, Taxes, and Accounting
    3.10.1  Overview
    3.10.2  Inputs
    3.10.2.1  Enterprise Data
    3.10.2.2  Interest Rates
    3.10.2.3  Outputs From Cash Flow Components of the Stress Test
    3.10.3  Procedures
    3.10.3.1  New Debt and Investments
    3.10.3.2  Dividends
    3.10.3.3  Allowances for Loan Losses and Other Charge-Offs
    3.10.3.4  Operating Expenses
    3.10.3.5  Taxes
    3.10.3.6  Accounting
    3.10.4  Output
    3.11 Treatment of New Enterprise Activities
    3.12  Calculation of the Risk-Based Capital Requirement
    3.12.1  Overview
    3.12.2  Inputs
    3.12.3  Procedures
    3.12.4  Output

1.0  Identification of the Benchmark Loss Experience

    OFHEO will use the definitions, data, and methodology described 
below to identify the benchmark loss experience.

1.1  Definitions

    The terms defined at Sec. 1750.11 shall apply for this Appendix. 
In addition, the term Origination year means the year in which a 
loan is originated.

1.2  Data

    [a] OFHEO identifies the benchmark loss experience using 
historical loan-level data required to be submitted by each of the 
two Enterprises. OFHEO's analysis is based entirely on the most 
current data available on conventional, 30-year, fixed-rate loans 
secured by first liens on single-unit, owner-occupied, detached 
properties. Detached properties are defined as single family 
properties excluding condominiums, planned urban developments, and 
cooperatives. The data includes only loans that were purchased by an 
Enterprise within 12 months after loan origination and loans for 
which the Enterprise has no recourse to the lender.
    [b] OFHEO organizes the data from each Enterprise to create two 
substantially consistent data sets. OFHEO separately analyzes 
default and severity data from each Enterprise. Default rates are 
calculated from loan records meeting the criteria specified above. 
Severity rates are calculated from the subset of defaulted loans for 
which loss data are available.

1.3  Procedures

    1.3.1  Cumulative 10-year default rates for each combination of 
states and origination years (state/year combination) that OFHEO 
examines are calculated for each Enterprise by grouping all of the 
Enterprise's loans originated in that combination of states and 
years. For origination years with less than 10 years of loss 
experience, cumulative-to-date default rates are used. The two 
Enterprise default rates are averaged, yielding an ``average default 
rate'' for that state/year combination.
    1.3.2  An ``average severity rate'' for each state/year 
combination is determined in the same manner as the average default 
rate. For each Enterprise, the aggregate severity rate is calculated 
for all loans in the relevant state/year combination and the two 
Enterprise severity rates are averaged.
    1.3.3  The ``loss rate'' for any state/year combination examined 
is calculated by multiplying the average default rate for that 
state/year combination by the average severity rate for that 
combination.
    1.3.4  The default and severity behavior of loans in the state/
year combination containing at least 2 consecutive origination years 
and contiguous areas with a total population equal to or greater 
than 5 percent of the population of the United States with the 
highest loss rate constitutes the benchmark loss experience.

2.0   Identification of a New Benchmark Loss Experience

    OFHEO will periodically monitor available data and reevaluate 
the benchmark loss experience using the methodology set forth in 
this Appendix. Using this methodology, OFHEO may identify a new 
benchmark loss experience that has a higher rate of loss than the 
benchmark experience identified at the time of the issuance of this 
regulation. In the event such a benchmark is identified, OFHEO may 
incorporate the resulting higher loss rates in the stress test.

3.0  Computation of Risk-Based Capital Level

    3.1  Enterprise Data
    3.1.1  Overview
    [a] The stress test requires data on all of an Enterprise's 
assets, liabilities, stockholders equity, and off-balance sheet 
obligations, as well as the factors that affect them: interest 
rates, house prices, rent growth rates, and vacancy rates. This 
section characterizes proprietary data of the Enterprises (as 
opposed to publicly available data) that are necessary for the 
stress test, which are primarily data on Enterprise portfolios of 
financial instruments and guarantees as of the start of the stress 
test. Data available from public sources that are also necessary for 
the stress test--e.g., historical interest rates, house price growth 
rates, and public securities data \1\--are described in the sections 
of this Appendix that describe the related components of the stress 
test (e.g., the Interest Rate component). The stress test uses 
proprietary and public data directly, and also uses values derived 
from such data. The derivation of these additional values are also 
explained in sections of this Appendix. All data as of the start of 
the stress test, proprietary data of the Enterprises and public 
data, are ``starting position data.''
---------------------------------------------------------------------------

    \1\ Data elements listed below for non-mortgage financial 
instruments are available from public sources for publicly traded 
securities, but are proprietary for privately placed instruments, in 
particular, derivative contracts.
---------------------------------------------------------------------------

    [b] Starting position data include, for all the loans owned or 
guaranteed by an Enterprise, as well as securities and derivative 
contracts, the dollar balances of these instruments and obligations, 
as well as all characteristics that bear on their behavior under 
stress test conditions. Data are required for the following 
categories of instruments and obligations:
     Mortgages owned by or underlying mortgage-backed 
securities issued by the Enterprises (``whole loans'')
     Mortgage-related securities

[[Page 18220]]

     Non-mortgage-related securities, whether issued by an 
Enterprise, e.g., debt, or held as investments
     Derivative contracts
     Other off-balance sheet guarantees (e.g., guarantees of 
private-issue securities)
    [c] The stress test also requires starting position data for 
``non-cash'' balance sheet items, such as premiums and discounts, 
that affect pro forma financial statements through the ten-year 
stress period.

3.1.2  Whole Loans

    [a] Whole loans are individual single family or multifamily 
mortgage loans. The stress test distinguishes between whole loans 
that the Enterprises hold in their investment portfolios (retained 
loans) and those that underlie mortgage-backed securities (sold 
loans). Data are aggregated for loans with similar portfolio 
(retained or sold), risk, and product characteristics. The 
characteristics of these ``loan groups'' determine mortgage default, 
prepayment, and loss severity rates, and cash flows.
    [b] The characteristics that are the basis for loan groupings 
are called ``classification variables'' and reflect categories, 
e.g., fixed interest rate versus floating interest rate, or identify 
a value range, e.g., original loan-to-value ratio greater than 80 
percent and less than or equal to 90 percent. After the loans are 
grouped, weighted average values for characteristics of the loan 
group are calculated, e.g., weighted average loan coupon (WAC) and 
weighted average remaining maturity (WAM). Loan group 
characteristics are used as inputs in section 3.5, Mortgage 
Performance, of this Appendix to determine mortgage performance 
(default, prepayment, and loss severity) and mortgage cash flows.

3.1.2.1  Characteristics Used to Create Loan Groups

    [a] Loan groups are formed based on the values, as of the start 
of the stress test, of the relevant loan classification variables 
shown in Table 3-1.

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[GRAPHIC] [TIFF OMITTED] TP13AP99.246



[[Page 18223]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.247



[[Page 18224]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.248


    [b] All loans with the same values for each of the relevant 
characteristics included in Table 3-1 above comprise a single loan 
group; for example, one loan group would include all loans with the 
following characteristics:
     Single family
     Sold portfolio
     30-year fixed-rate conventional
     Originated in 1997
     LTV greater than 75 percent and less than or equal to 
80 percent
     Original coupon greater than or equal to six percent 
and less than seven percent
     Starting coupon (coupon at the start of the stress 
period) greater than or equal to six percent and less than seven 
percent
     Secured by property located in the East North Central 
Census division
     Subject to a remittance cycle where scheduled principal 
and interest payments are held for an average of seven days

3.1.2.2 Loan Group Characteristics

    In addition to the classification variables used for grouping 
loans, the stress test requires values for characteristics 
calculated for the loans within each group. All values are as of the 
start of the stress test. Except as indicated in the ``Description'' 
column, values are averages for the loans comprising a loan group, 
weighted by their unpaid principal balances (UPB).

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[[Page 18226]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.250



3.1.2.3  Individual Loan Data

    The stress test requires data for individual loans in an 
Enterprise's portfolio in order to determine the characteristics of 
loans that (for purposes of the stress test) fulfill commitments 
that are outstanding at the start of the stress period, and to 
compute loss coverage provided by credit enhancements such as 
private mortgage insurance. These data requirements are listed 
below.

3.1.2.3.1  Commitments Data

    [a] To establish the characteristics of loans that fulfill 
commitments so that they are consistent with the characteristics of 
loans securitized by an Enterprise that were recently originated, 
data are required for loans that meet the following criteria:
     Single family
     Originated within six months of the start date of the 
stress test
     Securitized
     One of the following product types:
    1. 30-year fixed-rate
    2. 15-year fixed-rate
    3. One-year CMT ARM
    4. Seven-year balloon
    [b] For these loans, the following data are required:
     Loan balance as of the beginning of the stress period
     Original LTV
     Census division
     Guarantee fee
     Servicing fee
     Margin (for ARM loans)
     Credit enhancement data described in section 3.1.2.3.2, 
Credit Enhancement Data, below
    [c] The dollar amount of commitments outstanding at the start of 
the stress test is also required.

3.1.2.3.2  Credit Enhancement Data

    [a] To facilitate calculation of the reductions in mortgage 
credit losses due to credit enhancements, the following data are 
required for all credit-enhanced loans, if any, in a loan group:
    1. Type of mortgage credit enhancement:
    a. Private mortgage insurance
    b. Recourse
     Limited
     Unlimited
    c. Indemnification
     Limited
     Unlimited
    d. Pool insurance
    e. Spread account
    f. Collateral posted under collateral pledge agreement
    g. Cash account
    2. Private mortgage insurance coverage percent
    3. Loan balance as of the beginning of the stress period
    4. Public rating of mortgage insurer
    5. Public rating of pool insurer
    6. Public rating of seller or servicer
    [b] The following additional information is needed for each loan 
delivery contract involving a spread account, collateral account, 
cash, limited recourse or indemnification, or pool insurance account 
(e.g., a particular contract for the delivery of $100 million of 
loans may specify the establishment of a spread account as credit 
enhancement):
     Coverage remaining, as of the beginning of the stress 
period
     Account balance(s) at the start of the stress period
     Coverage expiration date

3.1.2.4  Single Family Mortgage Portfolio-Wide Information

    To reflect the differential performance of single family 
mortgages on investor-owned and owner-occupied properties, the 
stress test also requires data on the percentage of first lien 
mortgages in the combined retained and sold portfolios financing 
investor-owned properties.

3.1.3  Mortgage-Related Securities

    [a] The Enterprises hold mortgage-related securities as assets. 
These securities include single class and derivative mortgage-backed 
securities (multi-class and strip securities) issued by Fannie Mae, 
Freddie Mac, and Ginnie Mae; mortgage revenue bonds issued by State 
and local governments and their instrumentalities; and single class 
and derivative mortgage-backed securities issued by private 
entities. Most mortgage-related securities are collateralized by 
single family mortgages, others by multifamily mortgages, and, for 
the purposes of the stress test, still others by housing-related 
assets such as manufactured housing loans.
    [b] The stress test models the cash flows of these securities 
individually. Enterprise data required for this purpose are 
described below.

3.1.3.1  Single Class MBS Issued by the Enterprises and Ginnie Mae

    [a] Table 3-3 provides Enterprise data regarding each MBS held 
in their portfolios. This information is necessary for simulating 
cash flows in the stress test.

[[Page 18227]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.251


    [b] The Enterprises and Ginnie Mae make available to the public 
monthly pool data that provide investors with information on 
principal payments, as well as extensive data characterizing 
individual MBS and their underlying mortgage pools. These data, 
which are necessary to simulate MBS cash flows, are listed in 
section 3.9.2, Mortgage-Related Securities, of this Appendix.

3.1.3.2  Derivative Mortgage Securities Issued by the Enterprises and 
Ginnie Mae

    [a] Table 3-4 provides Enterprise data regarding REMICs and 
Strips issued by the Enterprises or Ginnie Mae. This information is 
necessary for determining associated cash flows.
[GRAPHIC] [TIFF OMITTED] TP13AP99.252

    [b] The data in Table 3-4 identify individual securities that 
are held by the Enterprises in their portfolios, as well as the 
REMIC or Strip transaction associated with individual securities. 
Public securities disclosure information is the source of data on 
the collateral underlying the securities (e.g., pool numbers of 
securities comprising collateral for a series of securities) and the 
rules governing security cash flows. (See section 3.9.2, Mortgage-
Related Securities, of this Appendix.)

3.1.3.3  Mortgage Revenue Bonds and Miscellaneous Mortgage-Related 
Securities

    [a] Table 3-5 provides Enterprise data regarding mortgage 
revenue bonds and private-issue, mortgage-related securities (MRS). 
This information is necessary for determining associated cash flows.
[GRAPHIC] [TIFF OMITTED] TP13AP99.253


[[Page 18228]]


    [b] The data in Table 3-5 are supplemented with public 
securities disclosure data, as described in section 3.9.2, Mortgage-
Related Securities, of this Appendix.

3.1.4  Non-Mortgage Financial Instruments

    [a] Non-mortgage financial instruments include debt securities 
issued to fund assets, debt securities and preferred stock held as 
assets, derivatives contracts (interest rate swaps, caps, and 
floors), and preferred stock issued by an Enterprise. Cash flows for 
non-mortgage financial instruments are simulated based on their 
characteristics. Although information for publicly traded 
securities, including most of the Enterprises' debt securities and 
non-mortgage investments, is available from public securities 
disclosure documents, information on other derivative contracts and 
non-publicly traded instruments must be obtained from the 
Enterprises. Data categories listed here apply to both publicly 
traded and privately placed instruments. All data are instrument 
specific; the pay- and receive-sides of swap contracts are treated 
as separate instruments. Table 3-6 provides basic information about 
non-mortgage financial instruments input variables, as follows:
[GRAPHIC] [TIFF OMITTED] TP13AP99.254


[[Page 18229]]


    [b] Occasionally, instruments have complex or non-standard 
features, and cash flows cannot be computed using the basic data 
listed above. In these cases the accurate modeling of cash flows 
requires additional information, such as amortization schedules, 
interest rate coupon reset formulas, and the terms of European call 
options, which is obtained from the Enterprises (and is included in 
public securities disclosure materials for publicly offered 
securities).

3.1.5  Operations, Taxes, and Accounting

    The stress test determines how much total capital an Enterprise 
must hold at the start of the stress test so that total capital 
never falls below zero during the stress period. To accomplish this 
objective, projected cash flows for Enterprise financial instruments 
must be supplemented by projected operating expenses, taxes, and 
capital distributions. All of these must be recorded in pro forma 
financial statements in order to determine an Enterprise's total 
capital for each month of the stress period. Thus, complete 
information on the Enterprise balance sheet as of the start of the 
stress period is required. The necessary information is listed in 
section 3.1.5.1, Data Required to Calculate Taxes, Operating 
Expenses, and Dividends, below.

3.1.5.1  Data Required to Calculate Taxes, Operating Expenses, and 
Dividends

    The following Enterprise data are necessary to calculate taxes, 
operating expenses, and dividends:
     Operating expenses (e.g., administrative expenses, 
salaries and benefits, professional services, property costs, 
equipment costs) for the quarter prior to the beginning of the 
stress test
     Earnings before income taxes and provision for income 
taxes for the three years prior to the beginning of the stress 
period
     Year-to-date income before taxes and provision for 
income taxes
     Dividend payout ratio for the four quarters prior to 
the beginning of the stress period
     Minimum capital requirement as of the beginning of the 
stress period

3.1.5.2  Balance Sheet as of the Start of the Stress Test

    The data are necessary to create Enterprise balance sheets as of 
the start of the stress period are described below.
    1. Balances for all instruments for which the stress test 
calculates cash flows. These are included with data the Enterprises 
provide for cash flow calculations. Balances are required for:
     Whole loans
     Mortgage-related securities
     Non-mortgage investments and investment-linked 
derivative contracts
     Debt and related cash flows
    2. Additional starting position balances:
     Amounts required to reconcile starting position 
balances from cash flow components of the stress test with an 
Enterprise's balance sheet (for example, differences between actual 
and estimated loan prepayments during the last few days in the 
month)
     Cash
     Low income housing tax credit investments
     Unamortized balances of premiums, discounts, and fees 
from the acquisition of retained loans and mortgage-related 
securities at other than par value
     Allowances for loan losses
     Accrued interest receivable on retained loans, 
mortgage-backed securities, mortgage-linked derivatives, and non-
mortgage investments
     Amounts receivable from Index Sinking Fund Debentures, 
currency swaps, fees, income taxes, and other accounts receivable
     Real estate owned (REO)
     Fixed assets
     Clearing accounts
     Unamortized premiums, discounts, and fees related to 
debt securities
     Unamortized balances related to the sold portfolio
     Deferred balances related to liability-linked 
derivatives
     Accrued interest payable
     Principal and interest payable to mortgage security 
investors
     Other liabilities, including payables from currency 
swaps, escrow deposits income taxes
     Dividends payable
     Components of stockholder's equity (i.e., common stock, 
preferred stock, paid-in capital, retained earnings, treasury stock, 
and unrealized gains and losses on available-for-sale securities)

3.1.6  Other Off-Balance-Sheet Guarantees

    In addition to the MBS they issue, the Enterprises guarantee 
other securities. The stress test does not simulate the cash flows 
associated with these guarantees, but it does calculate an 
incremental capital requirement for them. This calculation requires 
Enterprise information on the sum of the outstanding balances of all 
tax-exempt multifamily housing bonds, single-family whole-loan 
REMICs, multifamily whole-loan REMICs, and similar instruments or 
obligations as of the beginning of the stress period (excluding all 
guarantees of securities where 100 percent of collateral is insured 
by FHA or guaranteed by VA).\2\
---------------------------------------------------------------------------

    \2\ These include: (1) Any guarantee, pledge, purchase 
arrangement, or other obligation or commitment provided or entered 
into by an Enterprise with respect to multifamily mortgages to 
provide credit enhancement, liquidity, interest rate support, and 
other guarantees and enhancements for revenue bonds issued by a 
state or local government unit (including a housing finance agency) 
or other bond issuer; and (2) all off-balance-sheet obligations of 
an Enterprise that are not mortgage-backed securities or 
substantially equivalent instruments and that are not resecuritized 
mortgage-backed securities, such as real estate mortgage investment 
conduits or similar resecuritized instruments. See 12 CFR 1750.2.
---------------------------------------------------------------------------

3.2  Commitments

3.2.1  Overview

    The Enterprises make contractual commitments to their customers 
to purchase or securitize mortgages. The stress test provides for 
deliveries of mortgages under the commitments that exist at the 
start of the stress period. It also determines all of the relevant 
characteristics of these mortgages by reference to the 
characteristics of the mortgages securitized by the Enterprise that 
were originated in the six months preceding the start of the stress 
period. Based on this information, the Commitments component of the 
stress test creates loan groups with coupon rates that vary based 
upon the interest rate scenario. These loan groups are added to the 
Enterprise's sold portfolio and the stress test projects their 
performance during the stress period. In the down-rate scenario, the 
stress test provides that 100 percent of the mortgages specified in 
the commitments are delivered. In the up-rate scenario, 75 percent 
are delivered. Loans are delivered over the first three months of 
the stress period in the down-rate scenario and the first six months 
in the up-rate scenario.

3.2.2  Inputs

    The stress test uses two sources of data to determine the 
characteristics of the mortgages delivered under commitments. One is 
information from the Enterprises on commitments outstanding at the 
start of the stress period and deliveries of loans originated in the 
six months preceding the start of the stress period (See section 
3.1.2, Whole Loans, of this Appendix). The other is interest rate 
series generated by the Interest Rates component of the stress test 
(See section 3.3, Interest Rates, of this Appendix).

3.2.2.1  Loan Data

    [a] To determine the total dollar amount of mortgages that will 
be delivered under commitments during the course of the stress 
period, the Enterprises are required to provide the total dollar 
amount of all commitments outstanding to purchase or securitize 
mortgages at the start of the stress period. In addition, to 
determine the composition of mortgages delivered to fulfill 
commitments, the stress test identifies loans that meet all of the 
following criteria:
     Business type-single family
     Origination date-within six months of the start date of 
the stress test
     Portfolio type-securitized
     Product type-one of the following:
    1. 30-year fixed-rate
    2. 15-year fixed-rate
    3. One-year CMT ARM
    4. Seven-year balloon
    [b] For the selected loans, the following loan-level information 
are required:
     Starting UPB
     Original LTV
     Census division
     Guarantee fee
     Margin (for ARM loans)
     Servicing fee

3.2.2.2 Interest Rate Data

    The stress test uses the following interest rate series, 
generated by the Interest Rates component, (See section 3.3, 
Interest Rates, of this Appendix) for the first 12 months of the 
stress period:
     One-year CMT rate
     Conventional 30-year fixed-rate mortgage rate
     Conventional 15-year fixed-rate mortgage rate
     Seven-year balloon mortgage rate \3\
---------------------------------------------------------------------------

    \3\ The stress text assumes that mortgage interest rates on 
seven-year balloon mortgages are 50 basis points less than 30-year 
conventional mortgage rates in the down-rate environment, and equal 
to the 30-year rate in the up-rate environment.

---------------------------------------------------------------------------

[[Page 18230]]

3.2.3  Procedures

    [a] Based on the characteristics of the mortgages securitized by 
the Enterprise that were originated in the six months preceding the 
start of the stress period and the interest rate projections in the 
stress period, the stress test determines all of the relevant 
characteristics of the loans delivered under the commitments that 
exist at the start of the stress test. Using this information and 
the classification variables-business type, portfolio type, product 
type, original loan-to-value ratio, and Census division, the stress 
test creates loan groups for commitments in the same manner as loan 
groups are created for other loans (specified in section 3.1.2, 
Whole Loans, of this Appendix). One exception is that the stress 
test uses an additional classification variable--delivery month--to 
form subgroups within each commitment loan group. This variable is 
used to create origination dates, which are the same as delivery 
dates for these loan groups. The procedures to create commitment 
loan groups are as follows.
    1. Establish the values for classification variables--business 
type, portfolio type, product type, original loan-to-value ratio, 
and Census division as defined in section 3.1, Enterprise Data, of 
this Appendix.
    2. Aggregate the loan-level information for the mortgages 
identified above into loan groups by the classification variables.
    3. Concurrently with step 2, compute total starting UPB, the UPB 
weighted average Original LTV, Servicing fee, Guarantee fee, and 
Margin (for ARM loans) for each loan group.
    4. Using loan group information from step 3, calculate the 
percent of total balance of all commitment loan groups for each loan 
group as follows:

% of total balance = total starting UPB for the loan group (from 
step 3 above)  total starting UPB for all commitment loan 
groups added together

    5. For each loan group, set the loan term and amortization 
period as shown in Table 3-7.
[GRAPHIC] [TIFF OMITTED] TP13AP99.255

    6. For each loan group, set remittance cycle to the shortest 
available option for the Enterprise.
    [b] Procedures for adding subgroup characteristics to each loan 
group are described below.
    1. Establish values for the subgroup classification variable--
delivery month using percentages from Table 3-8, and divide each 
loan group into subgroups, one for each delivery month. Three 
subgroups are created in the down-rate scenario, and six subgroups 
are created in the up-rate scenario.
    2. The total starting UPB for the subgroup is calculated as 
follows: subgroup balance = total dollar amount of commitments 
outstanding  x  % of total balance of the subgroup (from step 4 
above)  x  Percent delivered in that delivery month (from Table 3-
8).
[GRAPHIC] [TIFF OMITTED] TP13AP99.256

    3. Set the original coupon rate and starting coupon rate (as of 
delivery date) for each subgroup as set forth in Table 3-9.

[[Page 18231]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.257


    4. Based on the original coupon rate and starting coupon rate 
set for the subgroup in step 3, assign the subgroup with original 
coupon rate class value and starting coupon rate class value as 
defined in section 3.1.2, Whole Loans, of this Appendix.
    5. Set the origination year and month of the subgroup by adding 
the delivery month to the starting date of the stress period.
    6. Set the age of the subgroup in the stress period to the 
number of months elapsed in the stress period minus the delivery 
month. Set the remaining term of the subgroup to the amortization 
term minus the age of the subgroup.
    7. Set the net yield of the subgroup to the starting coupon rate 
minus the servicing fee.
    8. Set the passthrough rate of the subgroup to the net yield 
minus the guarantee fee.

3.2.4  Output

    [a] The output of the Commitment component of the stress test is 
data for a set of loan subgroups that are virtually identical to 
loan groups created for loans on the books of business of the 
Enterprises at the start of the stress test, except that an 
additional classification variable, delivery month, is used to 
supplement origination year for each subgroup of commitment loans. 
This additional information tells when the mortgages in that 
particular subgroup are delivered to the Enterprise.
    [b] The data for loan subgroups created by the Commitments 
component of the stress test allows the stress test to project the 
defaults, losses, prepayments, scheduled amortization, interest 
payments, guarantee fee income, and float income for loans purchased 
under commitments for the ten-year stress period.

3.3  Interest Rates

3.3.1  Overview

    The 1992 Act specifies changes in the ten-year constant maturity 
Treasury yield (CMT) for the two interest rate scenarios of the 
stress test. It further states that yields of Treasury instruments 
with other maturities will change relative to the ten-year CMT in 
patterns that are reasonably related to historical experience. The 
Interest Rates component of the stress test projects these Treasury 
yields as well as other interest rate indexes that are needed to 
calculate cash flows, to simulate mortgage performance for mortgages 
and other financial instruments, and to calculate the risk-based 
capital requirement. The Interest Rates component produces values 
for the interest rates and indexes for the starting date of the 
stress test and for each of the 120 months in the stress period. The 
process for determining interest rates can be divided into five 
steps. First, identify values for the necessary interest rates and 
indexes on the starting date. Second, project the ten-year CMT for 
each month of the stress period as specified in the 1992 Act. Third, 
project the one-, two-, three-, and six-month Treasury yields and 
the one-, two-, three-, five-, 20-and 30-year CMTs.\4\ Fourth, 
project non-Treasury indexes and interest rates. Fifth, project 
borrowing rates for the Enterprises.
---------------------------------------------------------------------------

    \4\ For ease of discussion, all of the Treasury yields are 
referred to as CMTs.
---------------------------------------------------------------------------

3.3.2  Inputs

    Projecting interest rates and indexes in the stress test 
requires initial values as of the start date of the stress test. 
Initial values for the stress test are the averages of the values 
for the month preceding the start of the stress period. Additional 
months of historical data are input to the stress test in order to 
project interest rates other than the ten-year CMTs during the 
stress period. The historical data input for non-Treasury interest 
rate indexes are listed in Table 3-12. Table 3-10 below contains a 
list and a description of the interest rates and indexes input to 
the stress test.

[[Page 18232]]

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[[Page 18233]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.259



3.3.3  Procedures

3.3.3.1  Identify Starting Values

    The starting values for all of the interest rates and indexes 
listed in Table 3-10 are their daily averages during the month 
preceding the start of the stress test.

3.3.3.2  Project the Ten-Year CMT

    The 1992 Act specifies that the stress test be based on 
increases or decreases in the ten-year CMT, whichever would require 
more capital. The ten-year CMT increases or decreases during the 
first year of the stress period and remains at that level for the 
remainder of the stress period. The 1992 Act further specifies how 
the increases and decreases in the ten-year CMT are determined.

3.3.3.2.1  Down-Rate Scenario

    [a] To determine the ten-year CMT in the down-rate scenario, the 
stress test first computes the average of the ten-year CMT for the 
nine months prior to the start of the stress test, and subtracts 600 
basis points; and second, computes the average yield of the ten-year 
CMT for the 36 months prior to the start of the stress test, and 
multiplies by 60 percent.
    [b] The ten-year CMT in the down-rate scenario is decreased to 
the lesser of these two yields unless that yield is less than 50 
percent of the average for the nine months preceding the start date. 
In that case, the ten-year CMT decreases 50 percent of the nine-
month average described above.
    [c] Once the ten-year CMT for the down-rate scenario is 
determined, the stress test decreases the ten-year CMT from the 
value as of the start of the stress period to this level in equal 
increments over the first twelve months of the stress period. The 
ten-year CMT remains at this level for the remaining nine years of 
the stress period.

3.3.3.2.2  Up-Rate Scenario

    [a] To determine the ten-year CMT in the up-rate scenario, the 
stress test first computes the average for the ten-year CMT the nine 
months prior to the start of the stress test, and adds 600 basis 
points; and second, computes the average for the ten-year CMT for 
the 36 months prior to the start of the stress test, and multiplies 
by 160 percent.
    [b] The ten-year CMT in the up-rate case is equal to the greater 
of these two rates unless that yield is greater than 175 percent of 
the average for the nine months preceding the stress period. In that 
case, the ten-year CMT increases to 175 percent of the nine-month 
average.
    [c] Once the ten-year CMT for the up-rate scenario is 
determined, the stress test increases the ten-year CMT from the 
value as of the start of the stress period to this level in equal 
increments over the first twelve months of the stress period. The 
ten-year CMT remains at this level for the remaining nine years of 
the stress period.

3.3.3.3  Project the Ten Other CMTs

    In the third step, yields for the one-, two-, three-and six-
month and the one-, two, three-, five-, 20-and 30-year CMTs are 
projected.

3.3.3.3.1  Down-Rate Scenario

    [a] In the down-rate scenario, the ten other CMTs are calculated 
by first computing the long-term averages for the ten-year CMT and 
each of the ten CMTs, and then computing the ratios of the ten-year 
CMT long-term average to the ten other CMT long-term averages. The 
long-term averages are calculated over the period from May, 1986, 
through April, 1995. These are presented in Table 3-11 below. The 
stress test multiplies the ten-year CMT for the last nine years of 
the stress test by the appropriate ratio to create the six other 
CMTs for the last nine years of the stress test.

[[Page 18234]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.260


    [b] In the first twelve months of the stress period, the ten 
other CMTs are computed in a manner similar to the calculation of 
the ten-year CMT for that period. From its value at the start of the 
stress test, each of the ten other CMTs is decreased in equal steps 
in each of the first twelve months of the stress period until it 
reaches the appropriate level for the nine remaining years of the 
stress test.

3.3.3.3.2  Up-Rate Scenario

    In the up-rate scenario, the six other CMTs are equal to the 
ten-year CMT in the last nine years of the stress test. Each of the 
six other CMTs is increased in equal increments over the first 
twelve months of the stress test until it equals the ten-year CMT.

3.3.3.4  Project Non-Treasury Interest Rates

    [a] Table 3-12 presents the equations for projecting the non-
Treasury interest rates for each month of the stress test. These 
equations were developed using the percentage spread between the 
non-Treasury interest rate and the CMT with the same or similar 
maturity over a historical period \5\ and an ARIMA procedure 
(Autoregressive Integrated Moving Average).\6\ The stress test 
applies these equations to forecast the spreads between each non-
Treasury interest rate and the CMT from which it is estimated for 
the 120 months of the stress period. Finally, the stress test 
converts the projected values for the proportional spreads into rate 
and index levels. As used here, the percentage spread for the three-
month LIBOR rate, for example, is:
---------------------------------------------------------------------------

    \5\ Various historical data series have missing values.
    \6\ SAS ETS Users Guide, SAS Institute, 1993.
    [GRAPHIC] [TIFF OMITTED] TP13AP99.062
    
    [b] In Table 3-12, equations are grouped according to the 
Treasury maturity against which the spread was calculated. For 
example, the first group's spread was computed against the one-month 
Treasury yield. Where the dependent variable was estimated as a 
first difference, this is indicated in the Description column. ``T'' 
represents the spread variable.

[[Page 18235]]

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[[Page 18236]]

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3.3.3.5  Project Borrowing Rates

    The stress test adds a 50 basis point credit spread to the 
federal agency cost of funds index to project Enterprise borrowing 
costs for the last nine years of the stress period.

3.3.4  Output

    The output from the interest rate calculations are 120 monthly 
interest rate and index values for the projected eleven points on 
the Treasury yield curve (one-month, two-month, three-month, six-
month, one-year, two-year, three-year, five-year, ten-year, 20-year 
and 30-year) and the 20 non-Treasury yields.

3.4 Property Valuation

3.4.1 Overview

    [a] The Property Valuation component provides the monthly single 
family house price growth rates, rent growth rates, and rental unit 
vacancy rates that contribute to the determination of property 
values in the calculation of mortgage performance. The rates are 
those associated with the benchmark loss experience, the ten-year 
experience of loans originated in Arkansas, Louisiana, Mississippi, 
and Oklahoma during 1983 and 1984. The benchmark loss experience 
spans twelve years from the beginning of 1983, when the first 
benchmark loans were originated, through the end of 1994, ten years 
after the last benchmark loans were originated. The rates used in 
the stress test are those for the middle ten years of this period, 
1984 through 1993.
    [b] Single family house price growth rates are taken from the 
HPI series for the West South Central Census Division, which 
includes all of the benchmark states except Mississippi. House price 
growth rates are used to project single family mortgage performance. 
Rent growth rates and vacancy rates are taken from information for 
the major metropolitan areas in the four benchmark States, published 
by the Institute for Real Estate Management, and State level vacancy 
rates published by the Bureau of the Census. These rates are used to 
project multifamily mortgage performance.
    [c] As required by the 1992 Act, in the up-rate scenario, house 
price rates and rent growth rates may require adjustment for 
inflation. If the ten-year CMT rises more than 50 percent from the 
average yield during the nine months preceding the stress period, 
rates are adjusted upward to take into account the effect of 
inflation.
    [d] This section includes a description of the required inputs 
and procedures for inflation adjustments, and concludes with 
outputs. These outputs include tables of benchmark house price and 
rent growth rates unadjusted for inflation and rental vacancy rates. 
These rates will not change unless the benchmark loss experience 
changes.

3.4.2 Inputs

    The inputs required for adjusting house price and rent growth 
rates are:
     The average yield of the ten-year CMT for the nine 
months preceding the stress period, as computed in section 3.3, 
Interest Rates, of this Appendix)
     The highest 10-year CMT during the stress period, as 
computed in section 3.3, Interest Rates, of this Appendix

[[Page 18237]]

     Unadjusted house price and rent growth rates during the 
stress period, as shown in Tables 3-13 and 3-14 below

3.4.3 Procedures

    Inflation adjustments are applied over the final five years of 
the up-rate scenario stress test. The procedures are described 
below.
    1. Determine whether an adjustment is necessary. Multiply the 
average10-year CMT for the nine months preceding the stress period 
by 1.50, and subtract the product from the highest value of the10-
year CMT during the stress period. The difference is YD. If YD > 0, 
follow steps 2-4 to apply an inflation adjustment. Otherwise, use 
the rates provided in the Tables 3-13 and 3-14.
    2. Compute the adjustment. Use the following formula to compute 
the cumulative adjustment as if YD were to apply over 9 years and 2 
months: \7\
---------------------------------------------------------------------------

    \7\ If the ten-year CMT increases 75 percent over the base 
month, a 50 percent increase will be achieved by month eight. The 
full increase will be achieved by month twelve. On average, the 
difference YD will apply for 9 years and 2 months.
[GRAPHIC] [TIFF OMITTED] TP13AP99.063

[GRAPHIC] [TIFF OMITTED] TP13AP99.287

    3. Calculate the monthly inflation adjustment factors to apply 
to house price and rent rate growth rates. The cumulative adjustment 
is applied over the last five years of the stress period, and 
monthly adjustment factors are computed as follows:
    a. For house-price growth rates, the monthly adjustment factor 
is: \8\

    \8\ This factor is in continuous rate form (note use of natural 
logarithm) to be compatible with the house price growth rate series 
in Table 3-13.
[GRAPHIC] [TIFF OMITTED] TP13AP99.064

[GRAPHIC] [TIFF OMITTED] TP13AP99.288

    b. For rent growth rates, the monthly adjustment factor is: \9\

    \9\ This factor is in discrete rate form to be compatible with 
the rent growth rate series in Table 3-14.
[GRAPHIC] [TIFF OMITTED] TP13AP99.065

 [GRAPHIC] [TIFF OMITTED] TP13AP99.289

    4. Compute final monthly growth rates. Add the monthly inflation 
adjustment factors IHt and IRt to the house 
and rent growth rates for months 61 through 120. The resulting 
series will be inflation-adjusted growth rates.

3.4.4  Output

    [a] Monthly house price growth rates, rent growth rates, and 
rental vacancy rates are used by the Mortgage Performance components 
of the stress test (see section 3.5, Mortgage Performance, of this 
Appendix). If there are no inflation adjustments, the house price 
and rent growth rates in Tables 3-13 and 3-14 are used. If the 
inflation adjustment is necessary, then the adjusted growth rates 
are used.
    [b] House price growth rates are inputs to the Single Family 
Default and Prepayment and the Single Family Loss Severity 
components of the stress test (See sections 3.5.2 and 3.5.3 of this 
Appendix). The rent growth rates and vacancy rates are inputs to the 
Multifamily Default and Prepayment and Multifamily Loss Severity 
components (See sections 3.5.4 and 3.5.5 of this Appendix).

[[Page 18238]]

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[[Page 18239]]

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3.5  Mortgage Performance

3.5.1  General

    [a] The four components of the stress test that simulate various 
elements of mortgage performance are single family default and 
prepayment, single family loss severity, multifamily default and 
prepayment, and multifamily loss severity.
    [b] Figure 3-1 is a schematic overview of the basic structure of 
each mortgage performance component. Each mortgage performance 
component uses as inputs loan group starting position data, interest 
rate series from the Interest Rates component (see section 3.3, 
Interest Rates, of this Appendix), historical house-price indexes 
(HPI) and rental-price indexes (RPI) from government sources, and 
HPI and RPI growth and rental vacancy rate series for the stress 
period from section 3.4, Property Valuation, of this Appendix. These 
inputs are used to calculate the values of explanatory variables 
that are then used to compute monthly default, prepayment, and loss 
severity rates. These monthly default, prepayment, and loss severity 
rates are used to compute cash flows (refer to section 3.9, Cash 
Flows, of this Appendix).

[[Page 18241]]

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3.5.2  Single Family Default and Prepayment

3.5.2.1  Overview

    The stress test calculates conditional default and prepayment 
rates for single family mortgages for each month of the ten-year 
stress period. A conditional rate of default or prepayment refers to 
the percentage of the outstanding balance in a loan group that 
defaults or prepays during a given period of time. Computing default 
and prepayment rates requires information on the risk 
characteristics of a loans, historical and projected rates of 
interest, and the historical and projected rates of property value 
appreciation (or depreciation). Some of this information is used 
directly, while other information is combined together to create new 
variables for use in the default and prepayment rate calculations. 
In all, nine explanatory variables are used to determine default and 
prepayment rates for single family loans: mortgage age, mortgage age 
squared, original loan-to-value ratio, probability of negative 
equity, prepayment burnout, the percentage of investment property 
loans, relative interest rate spread, yield curve slope, and 
mortgage product-type. A statistical analysis of the relationship 
between the explanatory variables and historical default and 
prepayment rates was used to estimate the weights (also known as 
regression coefficients) associated with each variable. The selected 
weights are combined as described below to compute quarterly default 
and prepayment rates throughout the stress test period. The 
quarterly rates are then converted to monthly conditional default 
and prepayment rates and used by the cash flow component (See 
section 3.9, Cash Flows, of this Appendix) of the stress test to 
calculate monthly principal reductions resulting from defaults and 
prepayments, and to calculate default losses for each month in the 
ten-year stress period.

3.5.2.2  Inputs

    [a] There are three categories of data inputs for single family 
default and prepayment rate calculations: characteristics of loan 
groups, interest rates, and house price index values and 
volatilities.
    [b] The loan group characteristics used here are listed below 
with their

[[Page 18242]]

corresponding variable names, where relevant, as they appear in 
subsequent formulas:
     Product type
     Origination year (Y0)
     Origination month (required for loans delivered under 
commitments only)
     Census division (d)
     Origination LTV (LTV0)
     Origination UPB (UPB0)
     Original coupon interest rate (rc,0)
     Mortgage origination term, in months (To)
     Mortgage amortization term, in months (Ta)
     Remaining term, in months (Tr)
     Percentage of investor loans (P) (this refers to the 
percent of investor property loans in an Enterprise's entire loan 
portfolio)
    [c] The interest rate variables are listed below, along with 
their reference names as they appear in subsequent formulas:
     Conventional 30-year fixed-rate mortgage coupon rates 
(rf,q)
     One-year (Constant Maturity) Treasury yields 
(y12q)
     Ten-year (Constant Maturity) Treasury yields 
(y120q)
    [d] All interest rate series are provided by the Interest Rate 
component in monthly form. They are converted to quarterly series by 
taking simple averages of monthly values within each calendar 
quarter. Each interest-rate series represents 30 years of historical 
values, plus 10 years of stress test values. As described below in 
section 3.5.2.3, Procedures, of this Appendix, loans with 
origination years prior to 1979 are treated as having an origination 
year of 1979. Therefore, no interest rate variable values before 
that year are used. The conventional 30-year fixed-rate mortgage 
rate series does not begin until the second half of 1979, so values 
for the first two quarters of 1979 are equal to the third-quarter 
value.
    [e] House price growth rates are used to adjust the value of 
collateral properties before and during the stress period. Before 
the stress test is run, mortgages are seasoned using historical 
Census Division HPI series from the most recent OFHEO HPI report. 
House price growth rates for the stress period are determined as 
discussed in section 3.4, Property Valuation, of this Appendix. The 
two house price growth rate volatility parameters published in the 
OFHEO HPI Report, for each Census division, are also used, as 
described below. The volatility parameters measure the distribution 
of individual house price growth paths around the measured HPI 
value, as a function of the age of a mortgage.

3.5.2.3  Procedures

3.5.2.3.1  Overview

    Five general steps for generating default and prepayment rates 
for single family loans are repeated for each loan group throughout 
the stress period.
    1. Obtain the loan group characteristics, the interest rates, 
and the HPI index and volatility values.
    2. Using the loan characteristics and other input data, compute 
the values for the nine explanatory variables, by loan group, for 
each quarter of the stress period.
    3. Match the time series of explanatory variables for each loan 
group to associated regression weights (coefficients) for use in 
calculating default and prepayment rate series. Some of the 
variables are multiplied by the weights and then used in the default 
and prepayment rate calculations. These are called ``continuous'' 
variables, and they include age (and age squared), investor-property 
percent. Other variables are categorical and do not get multiplied 
by the weights. Rather, for these explanatory variables, one of 
several available weights is assigned based on the value-range or 
category of the explanatory variable value in each quarter. For 
categorical variables, the underlying values can change from quarter 
to quarter, and the weights used will also change, as the variable 
value moves from one category to another.
    4. Sum the results of Step 3--a combined set of weighted 
continuous variables and categorical variable weights for each 
quarter--to produce factors that go into default and prepayment rate 
calculations. The rate calculations use logistic probability 
formulas. Table 3-17 provides all weights needed to compute the 
default and prepayment rates for each product type. There is one set 
of beta () and gamma () weights for 30-year fixed-
rate mortgages, one set for adjustable rate mortgages, and one set 
for all other product types.
    5. Convert the quarter default and prepayment rates into monthly 
equivalent rates so that the stress test has monthly series for cash 
flow projections.

3.5.2.3.2  Explanatory Variables Calculations

    The following sections describe how each explanatory variable is 
calculated and how the weights are combined to compute default and 
prepayment rates for a group of single family loans of similar risk 
characteristics.

3.5.2.3.2.1  Mortgage Age (Aq)

    [a] The mortgage age in each quarter of the stress period is 
computed as:
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    [b] Loans with origination years prior to 1979 are treated as if 
they were originated in 1979. The age value and the squared value of 
age are used directly in the default and prepayment formula, along 
with their weights (coefficients).

3.5.2.3.2.2  Origination LTV (LTV0)

    The value of the original LTV for each loan group does not 
change throughout the stress test. Once it is matched to an 
LTV0 category in Table 3-17, the associated default and

[[Page 18243]]

prepayment weights are used throughout the stress test.\10\
---------------------------------------------------------------------------

    \10\ Note that Table 3-1 of this Appendix shows eight categories 
for original LTV ratio classes. The default and prepayment component 
of the stress test combines the last three categories into one 
category.
---------------------------------------------------------------------------

3.5.2.3.2.3  Probability of Negative Equity (PNEQq)

    [a] The probability of negative equity variable requires 
creating a time series of property values and amortizing loans to 
create updated LTV ratios throughout the stress period. The updated 
LTV ratios are used along with the standard deviations of house 
price growth paths to compute probabilities of negative equity. The 
probability of negative equity measures the percent of loans 
underlying a loan group that are likely to have negative equity 
positions, in each quarter of the stress period. The step-by-step 
process for computing the variable PNEQq follows. See 
Figure 3-2 for an overview of the derivation process.
    1. Create a time series of property values that extends from 
loan origination through the stress period as described below.
    a. Extend the historical HPI series for each of the nine Census 
divisions through the stress period by adding the growth rate 
factors (gi) that are described in section 3.4, Property 
Valuation, of this Appendix:
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    b. Create an index for average house value in each quarter of 
the stress period (Vq) using HPI values from the loan 
origination quarter and from each quarter of the stress period, by 
Census division:
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    The published HPI series begins in the first quarter of 1980. 
Values for the four quarters of 1979 are produced by OFHEO, but are 
not published. Table 3-16 provides these values, which are assigned 
to HPId,O for loans originating in 1979. Loans with 
origination years prior to 1979 are treated as if they were 
originated in 1979.

[[Page 18244]]

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    2. Amortize the average loan balance from loan origination 
through the stress period. This procedure does not use the current 
mortgage coupon rate at the start of the stress period, but rather 
creates a history of interest rate paths for the loan group, from 
origination, as if all adjustable rate mortgages are Constant 
Maturity Treasury ARMs, with one-year adjustment periods.
    a. Create the coupon interest rate series, rc,q. For 
fixed-rate mortgages, set rc,q = rc,0, 
(original coupon) for every quarter. However, for adjustable-rate 
mortgages, adjustments must be made over time, taking into account 
period and lifetime interest rate caps as follows:

First, set rc,q = rc,0 for q = {1,...,4}.
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    Then, for every fourth quarter of loan life, evaluate:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.069
    
    [GRAPHIC] [TIFF OMITTED] TP13AP99.294
    
When rc,q<(y12q +0.0275), then set:
rc,q+1...q+4 = min{(y12q + 0.0275), 
(rc,q + 0.02), (rc,0 + 0.05)}

When rc,q>(y12q +0.0275), then set:
rc,q+1...q+4 = max{(y12q + 0.0275), 
(rc,q-0.02), (rc,0-0.05)}

When rc,q = (y12q +0.0275), then set:
rc,q+1...q+4 = rc,q
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    b. Compute the monthly mortgage payment factor (PMTq) 
for each quarter of the stress period, q = {1,...,40} using the 
formula:

[[Page 18245]]

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    In this formula, LTV0 represents the original loan 
balance. Using LTV0 allows the UPB time series to be 
calculated in index form to match Vq. PMTq 
will be constant throughout the stress test for fixed-rate loans 
because rc,q is fixed at rc,0.
    c. Calculate a remaining loan balance index for the UPB 
outstanding at the beginning of each quarter of the stress period, 
UPBq, based on PMTq, Tr, and 
elapsed time in the stress period, q, using the formula:
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    3. Compute updated LTV ratios (LTVq) for each quarter 
of the stress period:
[GRAPHIC] [TIFF OMITTED] TP13AP99.072

    4. Compute the standard deviation of house price growth paths 
(d,q) around the HPId,q value. Limit 
the value of the age variable to avoid negative ``diffusion.'' 
Negative diffusion occurs when the variance of house prices declines 
over time. The quadratic formula used here for the standard 
deviation of individual house price index values will create 
negative diffusion unless age is limited. The age limit formula is 
found by solving the first derivative of the house price volatility 
variance with respect to age, for zero. This variance is the 
function under the root sign in the d,q equation 
below (but using Aq rather than MAq). The age 
limit gives the value of age for which the diffusion of house price 
growth is maximized. Once this age value is reached, the stress test 
then holds diffusion at the maximum value for the remainder of the 
life of the loan:
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[[Page 18246]]

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    5. Calculate the probability of negative equity in each stress 
period quarter:
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3.5.2.3.2.4  Burnout (Bq)

    [a] The prepayment ``burnout'' variable, Bq, 
indicates whether there have been at least two quarters of 
``significant refinance opportunities'' among the previous eight 
quarters of loan life. A mortgage undergoes a significant refinance 
opportunity when its coupon is at least two percentage points above 
the then-prevailing rate on 30-year mortgages. The rate on 30-year 
mortgages is always used as the benchmark for defining refinance 
opportunities, regardless of the type of mortgages being analyzed. 
Prepayment burnout is a binary variable--two quarters of significant 
refinance opportunities either occur or do not occur.
    [b] If Aq  8, then Bq=0. If 
Aq >8, then:
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3.5.2.3.2.5  Occupancy Status (OS)

    The occupancy status variable is the percentage of loans in an 
Enterprise portfolio that are investor-owned (rental) properties 
rather than owner-occupied properties. It is a constant value (OS) 
applied equally to all loan groups and in all stress period 
quarters, computed as follows:
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3.5.2.3.2.6  Relative Spread (RSq)

    The relative spread variable (RSq in the formula 
below) is the percentage spread between a loan's contract rate and 
the rate on 30-year fixed-rate mortgages in the current quarter of 
the stress test. The higher this percentage is, the more likely a 
loan is to prepay:
[GRAPHIC] [TIFF OMITTED] TP13AP99.077

3.5.2.3.2.7  Yield Curve Slope (YSq)

    The variable YS q in the formula below represents the 
slope of the yield curve. It is included in the prepayment 
calculations to represent different relationships between short-and 
long-term interest rates. Different yield curve slopes represent 
different relationships between short and long term interest rates, 
and these relationships impact incentives to refinance either into 
ARMs or into fixed-rate mortgages:
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[[Page 18248]]



3.5.2.3.2.8  Product Type Adjustment Factors

    Product types other than fixed-rate 30-year mortgages and ARMs 
receive unique product-specific adjustment factor weights in the 
stress test. These factors relate the default and prepayment risk of 
each product type to the fixed-rate 30-year mortgage. ARMs do not 
need a risk adjustment factor because they use separate default and 
prepayment equations. All products other than 30-year fixed-rate and 
adjustable-rate mortgages use the same pair of default and 
prepayment equations. The product types included in this combination 
grouping, which receive product-specific risk adjustment factors, 
are: 20-year fixed-rate, 15-year fixed-rate, balloon, government 
insured or guaranteed loans, and second mortgages. All loan products 
with payment changes, such as graduated payment mortgages, two-step 
mortgages, and buydown mortgages, are treated as ARMs and use the 
ARMs default and prepayment formulas without a product adjustment 
factor. Biweekly and reverse mortgages are included with standard 
monthly mortgages of similar term and do not therefore require 
separate adjustments. The adjustment factor values are provided in 
Table 3-17.

3.5.2.3.2.9  Benchmark Calibration Factor

    A calibration adjustment of 0.146 is added to each statistical 
default equation to reasonably relate current loan default rates to 
the historical benchmark experience. The value 0.146 is a weighting 
factor, not an explanatory variable.

3.5.2.3.3  Combining Explanatory Variables and Weights

    [a] Each explanatory variable outlined above has associated 
numerical weights that are used in default and prepayment rate 
calculations. These weights, which are the estimated coefficients 
from statistical regressions, are referred to here as beta factors, 
j, for default weights, and gamma factors, 
k, for prepayment weights. As mentioned above, 
there is also a constant weight for benchmark calibration. In 
addition, each statistical equation has a different regression 
constant. These constants appear as separate weights, not tied to 
any explanatory variables.
    [b] The weights are combined to compute two sums: 
Xq for defaults and Xq for 
prepayment as follows:
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    [c] The only explanatory variables for which both the variable 
and its weight are included in the formula above are age 
(Aq), age squared (A2q), occupancy status (OS) 
and burnout (Bq). For each of these variables, the 
variable value is multiplied by its weight, which can be found in 
Table 3-17. For other (categorical) explanatory variables, however, 
the weights are not accompanied by the actual values of the 
explanatory variables. For these variables the computed variable 
value is only used to identify the category to which it belongs so 
that a representative weight can be selected from the weight table 
(Table 3-17) of this Appendix. Only the obtained weight is included 
in the Xq and Xq formulas 
for these variables.

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[[Page 18250]]

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3.5.2.3.4  Calculating Default and Prepayment Rates

    The total weighting factors, Xq and 
Xq, are converted into quarterly default and 
prepayment probabilities using the following logistic probability 
equations:
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3.5.2.3.5  Monthly Default and Prepayment Rates

    To this point, all calculations involved creating quarterly time 
series of values throughout the ten-year stress period (40 
quarters). In this step, the quarterly conditional default and 
prepayment rates are converted into monthly rates as follows:

[[Page 18251]]

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3.5.2.4  Output

    Use the resulting 120 monthly conditional default and prepayment 
rates for each loan group to calculate monthly principal reductions 
resulting from defaults and prepayments, and to calculate default 
losses for each month in the ten-year stress period.

3.5.3  Single Family Loss Severity

3.5.3.1  Overview

    [a] The Single Family Loss Severity component of the stress test 
computes loss severity rates for single family mortgages that 
default in each month of the stress test. The loss severity rate is 
the net cost of a loan default expressed as a percentage of the 
unpaid principal balance (UPB) at the time of default. Based on 
various cost and revenue elements associated with a loan default, 
the stress test calculates loss severity rates as the present value 
(at default date) of the net cash flows that occur following the 
default date. Most cost and revenue elements are entered as constant 
rates across loan groups throughout the stress period. Two 
exceptions are proceeds from property disposition and asset funding 
costs. Proceeds are derived through a formula that uses both 
historical and stress period house price appreciation rates, and 
that accounts for loan amortization from origination through 
default. Funding cost of the defaulted mortgages and the resulting 
foreclosed properties is captured by discounting the loss severity 
elements, using a cost-of-funds interest rate that varies during the 
stress period. Loss severity rates throughout the stress period will 
also vary according to the application of percent-denominated credit 
enhancements (dollar-denominated credit enhancements are directly 
applied in the Cash Flow component of the stress test) and their 
associated credit ratings.
    [b] The inputs used to compute loss severity rates include 
several starting position loan group characteristics, counterparty 
credit risk factors, historical house price index series and stress 
period house price growth rates, house price appreciation volatility 
parameters, and stress test interest rate series. The output of loss 
severity rates for each loan group are used in the Cash Flow 
component of the stress test (see section 3.9, Cash Flows, of this 
Appendix) to calculate (dollar) default losses.

3.5.3.2  Inputs

    [a] The Single Family Loss Severity component of the stress test 
uses loan group characteristics as of the start of the stress test, 
including information on certain types of credit enhancements, and 
credit risk factors associated with counterparty rating categories 
(see section 3.6, Other Credit Factors, of this Appendix). In 
addition, it uses historical and stress period HPI series, house 
price appreciation volatility parameters, and one interest rate 
series (see section 3.4, Property Valuation, of this Appendix).
    [b] The particular loan group characteristics (refer to section 
3.1, Enterprise Data, of this Appendix for the definitions of these 
loan group characteristics), with associated variable names used in 
the procedures below, are:
     Product Type
     Portfolio (retained or sold portfolio)
     Origination Year (subscript ``y'')
     Origination Month (tm, for commitment loan 
groups only)
     Census Division (subscript ``d'')
     Starting Coupon (rc,s)
     Original Coupon (rc,0, only used for ARMs)
     Passthrough Rate (rp, for sold loans only)
     Original LTV (LTV0)
     Mortgage Age (As)
     Amortization Term (Ta)
     Credit Enhancement Coverage Type 1 (Cmi, PMI 
coverage rate)
     Credit Enhancement Coverage Type 2 (Crc, 
seller/servicer recourse coverage rate)
     Percent of UPB under ``AAA'' coverage in a loan group 
(CR)
     Percent of UPB under ``AA'' coverage in a loan group 
(CR)
     Percent of UPB under ``A'' coverage in a loan group 
(CR)
     Percent of UPB under ``BBB'' coverage in a loan group 
(CR)
    [c] Credit enhancement coverages, both Type 1 and Type 2, are 
reduced throughout the stress test according to ``haircuts,'' as 
defined in section 3.6, Other Credit Factors, of this Appendix. 
These haircuts represent percentage reductions to credit enhancement 
coverage due to the inability of a counterparty to meet its 
obligations under stressful conditions. The final (end-of-stress-
period) haircuts, by credit rating class (AAA, AA, A, and BBB), are 
obtained from section 3.6, Other Credit Factors, of this Appendix.
    [d] In addition, historical Census division HPI series and house 
price appreciation volatility parameters are obtained from the most 
recently available OFHEO HPI Report. The HPI series are used to 
update collateral property values to the beginning of the stress 
test. Property values are then updated during the stress period with 
monthly house price growth rates obtained from section 3.4, Property 
Valuation, of this Appendix. The historical volatility parameters 
are used with stress period property values to develop distributions 
of property values and levels of home equity within loan groups.
    [e] The final input used here is the six-month Federal agency 
cost-of-funds rate, for each month of the stress period (variable 
``rd,t''). This monthly series is generated by the 
interest rate component of the stress test (See section 3.3, 
Interest Rates, of this Appendix) and is used as the discount rate 
for computing the present value of the three major elements of the 
loss severity rate--defaulting UPB, net costs or proceeds associated 
with foreclosure, and net cash flows from holding and disposition of 
Real Estate Owned (REO) property.

3.5.3.3  Procedures

    [a] The process of deriving loss severity rates involves 
calculating the present value of three loss elements. The first loss 
element (PV1) is the amount of defaulting UPB. The second loss 
element (PV2) is the expense related to foreclosure, net of any 
mortgage insurance proceeds. The third loss element (PV3) combines 
post-foreclosure property expenses with proceeds from REO property 
disposition. Each of these three loss elements is computed as the 
present value (as of the default date) of the net cash flows 
occurring at a separate point in time--four months after default for 
the first loss element, 13 months after default for the second loss 
element, and 20 months after default for the third loss element. The 
present values of the three loss elements then are added together to 
derive an initial loss severity rate (NPV1). Finally, available 
seller/servicer recourse against the (initial) loss is applied to 
calculate the final loss severity rate (NPV3). Figure 3-3 of this 
Appendix depicts the timing of the three loss elements and how they 
are combined to produced initial and final loss severity rates.
    [b] In the procedures for calculating loss severity rates, loan 
amortization is performed each month for surviving loans in each 
loan group; all discounting of cash flows uses semi-annual 
compounding of interest rates; all calculations add expenses and 
subtract revenues to calculate loss severity rates; and all loss 
elements are calculated as percentages of the UPB of the defaulting 
loans. With the exception of computations for FHA and VA loans, 
calculations are not specific to any particular loan product types, 
although loan group characteristics (coupon rate and amortization 
term) are used in the severity calculations.
    [c] The lack of product type distinctions in severity 
calculation means that adjustable

[[Page 18252]]

rate mortgages are treated like fixed-rate mortgages. Their coupon 
rates are not updated during the stress test, and the original 
coupon is used to perform loan amortizations used in the statistical 
equation for property disposition proceeds. This simplification does 
not affect the actual defaulting UPB used to calculate dollar 
losses. The cash flow portion of the stress test does update coupon 
rates for adjustable rate products, and uses the updated rates to 
amortize loan group UPB. There are also no differences in loss 
severity rate calculations for investor loans. The stress test does 
not group loans according to occupancy status (owner-occupant versus 
investor/rental), although the statistical analysis used to derive 
the loss severity elements for the stress test used data on both 
occupancy status types. Thus, the loss severity elements shown here 
reflect a balance of owner-occupant and investor loans.
    [d] The stress test groups FHA and VA loans together. To 
calculate severity rates, FHA and VA insurance coverage amounts are 
calculated separately for all FHA/VA loan groups. Loan group credit 
enhancements are then calculated by summing the coverage amounts, 
with FHA insurance receiving a 0.67 weight and VA insurance 
receiving a 0.33 weight. Final loss severity rates for FHA/VA loan 
groups are then computed based on these weighted average coverage 
amounts.

3.5.3.3.1  Defaulting UPB

    The defaulting UPB is the first loss element included in the 
loss severity rate calculation. The stress test recognizes 
defaulting UPB four months after the month of default. At this 
point, the defaulting UPB is recognized as a loss severity element 
and a potential cost (pending offsetting revenues from mortgage 
insurance and property disposition). For sold loans, defaulting 
mortgages are first purchased from the security pools, requiring a 
cash outlay equal to the UPB. Because only sold loans involve actual 
cash outlays, sold and retained loans are treated slightly 
differently in this loss element calculation.
[GRAPHIC] [TIFF OMITTED] TP13AP99.374

    1. For sold loans, recognize the cash outlay by discounting UPB 
back to the date of default:
[GRAPHIC] [TIFF OMITTED] TP13AP99.084

[GRAPHIC] [TIFF OMITTED] TP13AP99.385

    2. For retained loans, set PV1t = 1 to represent the 
full UPB. No discounting is necessary because recognition of the 
defaulting UPB does not involve an actual cash outlay.

3.5.3.3.2  Net Costs or Proceeds Associated with Foreclosure

    The second loss element includes foreclosure related 
transactions. There are

[[Page 18253]]

several cash flows, so that multiple computations are required.
    1. Calculate survival factors for each counterparty rating 
category, for each month of the stress period. The monthly survival 
factors represent percentages of obligations that counterparties 
with given credit ratings are expected to meet as the stress period 
continues. They are derived from the final haircuts defined in 
section 3.6, Other Credit Factors, of this Appendix. These factors 
are applied here to private mortgage insurance (PMI) coverage, and 
later to seller/servicer recourse obligations. Survival factors for 
each credit rating category are constant across loan groups:
[GRAPHIC] [TIFF OMITTED] TP13AP99.085

[GRAPHIC] [TIFF OMITTED] TP13AP99.306

    2. Calculate private mortgage insurance (PMI) proceeds.
    a. Calculate the weighted average survival factor for each loan 
group. For each month, t, of the stress period, multiply the 
survival factor for each counterparty rating, SFR,t, by 
the percentage of the loan group UPB covered by counterparties with 
the same rating, CR. Sum the results across all 
counterparty ratings, R. Next, divide that sum by the sum of all 
counterparty coverage percentages. This produces a weighted average 
survival factor, SFw,t, by loan group, for each month, t, 
of the stress period:
[GRAPHIC] [TIFF OMITTED] TP13AP99.086

[GRAPHIC] [TIFF OMITTED] TP13AP99.307

    b. Multiply the weighted average survival factors, 
SFw,t, by the PMI percentage coverage rate, 
Cmi, to derive monthly adjusted percentage coverage 
rates, Cmi,t:
[GRAPHIC] [TIFF OMITTED] TP13AP99.087

[GRAPHIC] [TIFF OMITTED] TP13AP99.308

    c. Compute mortgage insurance proceeds (mit), by 
multiplying the adjusted PMI percentage coverage rate, 
Cmi,t, by the mortgage insurance claim amount. First, for 
all conventional loans--loan groups other than FHA/VA:
[GRAPHIC] [TIFF OMITTED] TP13AP99.088

    For FHA/VA loan groups, calculate the FHA insurance proceeds:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.089
    

[[Page 18254]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.309


    3. Discount all foreclosure related cash flows by 
tf=13 months to compute the post-foreclosure loss 
element, PV2t.
    a. For retained loans:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.090
    
    b. For sold loans, add passthrough interest expense to mortgage-
backed security holders for 4 months:
[GRAPHIC] [TIFF OMITTED] TP13AP99.091

    c. For FHA/VA loans:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.092
    
    [GRAPHIC] [TIFF OMITTED] TP13AP99.310
    
    4. Calculate the payment to the loan servicer (PVSt) 
net of any interest paid by the seller/servicer to the Enterprise 
that would be repaid in the post-foreclosure servicer claim. The 
present value factor generated here is not used in the computation 
of the foreclosure loss component, but will be used later to account 
for cases where there is full recourse to the seller/servicer. This 
is required only where there is Type 2 Credit Enhancement coverage. 
It is not used for FHA/VA loans. For retained loans:
[GRAPHIC] [TIFF OMITTED] TP13AP99.093

    For sold loans, add the (4 months) interest passed through by 
the Enterprise to security holders:

[[Page 18255]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.094


[GRAPHIC] [TIFF OMITTED] TP13AP99.311

3.5.3.3.3  Net Cash Flow from Holding and Disposition of REO Property

    The third loss element includes cash flows associated with 
management and disposition of REO property. Cash flows used in 
calculating this element are sales proceeds from disposition of 
foreclosed property and REO property management (maintenance and 
operating) expenses.

3.5.3.3.3.1  Calculate Proceeds From Property Sale

    Sales proceeds is a dynamic loss severity element whose 
calculation involves updating property values and loan balances over 
time. Several steps are required. First, property values and UPB are 
updated from origination to the time of default. This is done with 
index values, rather than dollar values. Property values are 
represented by a house price index, and loan balances by a UPB index 
(ratios of defaulting UPB to the original house price). Second, a 
statistical measure (z-score) of the distance between the logarithm 
of house price index and the logarithm of the loan balance index is 
calculated. Third, an econometric equation uses the z-score to 
compute the portion of UPB that is not recovered at property 
disposition. Finally, the unrecovered portion of UPB is converted 
into proceeds from property sale.
    1. Update property values.
    a. Calculate a house price index at the start of the stress 
test, according to origination year and Census division cohort:
[GRAPHIC] [TIFF OMITTED] TP13AP99.095

[GRAPHIC] [TIFF OMITTED] TP13AP99.312

    Because HPI values are as of the end of each quarter, 
HPId,-1 gives the value as of the start of the stress 
period. The OFHEO HPI is published beginning with the first quarter 
of 1980. OFHEO has also produced (but not published) values for 
earlier years. To season loans originating in 1979, assign 
HPId,q according to the Census division specific values 
listed in Table 3-16. Treat all pre-1979 originations as if they 
were originated in 1979.
    b. Calculate house price index values during the stress period 
by multiplying the Id,q by cumulative house price growth 
rates in the stress period:
[GRAPHIC] [TIFF OMITTED] TP13AP99.096

[GRAPHIC] [TIFF OMITTED] TP13AP99.313


[[Page 18256]]


    Do not calculate Id,q for loans that an Enterprise 
has committed to buy, but not yet purchased at the beginning of the 
stress period, because pre-stress period house price appreciation is 
not applicable. The house price index for these loans is the 
cumulative monthly growth rate from the month after delivery to the 
month of loss severity calculations (month of default):
[GRAPHIC] [TIFF OMITTED] TP13AP99.097

[GRAPHIC] [TIFF OMITTED] TP13AP99.314

    2. Calculate the standard deviation of house price growth paths, 
d,t, around the average growth path implied by 
the HPId,q,t value. This first requires limiting the 
value of the age variable to avoid negative ``diffusion.'' Negative 
diffusion occurs when the variance of house prices declines over 
time. While negative diffusion is not expected to happen in 
practice, the formula for the standard deviation of house price 
growth paths (which is a quadratic function of time, where the 
first-order term is positive and the second-order term is negative) 
will create negative diffusion unless age is limited.
    a. Create a variable for mortgage age in the stress test:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.098
    
    [GRAPHIC] [TIFF OMITTED] TP13AP99.315
    
    b. Create a mortgage age variable (MAt) that limits 
the mortgage age to a maximum value:
[GRAPHIC] [TIFF OMITTED] TP13AP99.099

[GRAPHIC] [TIFF OMITTED] TP13AP99.316

    c. Calculate the standard deviation of house price growth rate 
path using MAKt:
[GRAPHIC] [TIFF OMITTED] TP13AP99.100

[GRAPHIC] [TIFF OMITTED] TP13AP99.317

    3. Compute a monthly loan payment factor using the original 
coupon rate and original LTV (LTV0). Since original 
property value is specified to be equal to one, LTV0 
represents the original UPB. Use this payment factor to compute the 
time series of UPB index (see below) to capture amortization of 
surviving loans in each loan group throughout the stress period:
[GRAPHIC] [TIFF OMITTED] TP13AP99.101


[[Page 18257]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.318


    4. Calculate the time series of UPB index--the ratios of 
defaulting UPB in each month of the stress period to the original 
house price:
[GRAPHIC] [TIFF OMITTED] TP13AP99.102

[GRAPHIC] [TIFF OMITTED] TP13AP99.319

    5. Compute the z-score for the ``distance'' between the logarithm 
of the house price index and the logarithm of the UPB index. The use of 
logarithmic values allows each variable to be specified as a percentage 
difference from the original property value (1.0). This transformation 
makes the distance between the house price and UPB indexes consistent 
with the standard deviation of the house price growth rates used to 
calculate the z-score.\11\ The formula for the z-score is:
---------------------------------------------------------------------------

    \11\ This standard deviation is of cumulative house price growth 
rates. The log of HPI is the cumulative growth of average house 
prices in the geographic area, while the log of b gives an HPI-
growth-rate-equivalent interpretation to owner invested equity 
(downpayment plus amortization). The resulting log difference is the 
amount by which the individual house price growth must be lower than 
average market growth in order to eliminate any equity in the 
property and thus lead the borrower to consider default.
[GRAPHIC] [TIFF OMITTED] TP13AP99.103

[GRAPHIC] [TIFF OMITTED] TP13AP99.320

    The allowable values of zt are bounded by 4.0 and -
0.50. If the computed value zt is outside either of these 
bounds, it is reset to its closest boundary value.
    6. Compute the percentage of UPB that is not recovered at 
property disposition based on the statistically derived relationship 
between the percentage of UPB unrecovered at property disposition 
and the z-score:
[GRAPHIC] [TIFF OMITTED] TP13AP99.104


[[Page 18258]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.321


    Because log-transformed values of the unrecovered UPB 
(ln(Lt) + 1)) were used in the regression, the ``1'' in 
the equation above is a result of using the antilog to derive the 
formula for Lt. In addition, the formula also includes 
the calibration factor to reasonably relate loss severity rate to 
the benchmark experience.
    7. Calculate sales proceeds from the disposition of each 
foreclosed property, Pt, as UPB less the portion that was 
not recovered at disposition, Lt:
[GRAPHIC] [TIFF OMITTED] TP13AP99.105

[GRAPHIC] [TIFF OMITTED] TP13AP99.322

3.5.3.3.3.2  Net Cash Flow at Property Disposition

    Subtract sales proceeds from expenses related to REO property, 
then discount the result by (tf+ti = 20 
months) to obtain the present value of the third loss severity 
element:
[GRAPHIC] [TIFF OMITTED] TP13AP99.106

[GRAPHIC] [TIFF OMITTED] TP13AP99.107

or
[GRAPHIC] [TIFF OMITTED] TP13AP99.323

3.5.3.3.4  Final Calculations of Loss Severity Rates

    At this point, all cost elements of loss severity are included 
in PV1, PV2, and PV3. Revenues from private mortgage insurance (Type 
1 credit enhancement) or FHA insurance are also included in PV2. The 
sum of PV1, PV2, and PV3 then provides an initial net-present-value 
loss severity rate (NPV1). Once this is calculated, potential 
revenues from seller/servicer recourse (Type 2 credit enhancement) 
and VA insurance guaranty proceeds are computed. For non-government 
(conventional loans), the recourse proceeds are subtracted from NPV1 
to arrive at final loss severity rates (NPV3) for each loan group, 
in each month of the stress test. For FHA/VA loan groups, final loss 
severity rates are calculated using a weighted average of the 
proceeds from the two forms of government insurance.
    1. Calculate the initial loss rates (after mortgage insurance 
and FHA coverage, but before seller/servicer recourse or VA 
coverage):
[GRAPHIC] [TIFF OMITTED] TP13AP99.376


[[Page 18259]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.324


    2. Proceed based upon whether the loan group represents 
conventional or FHA/VA loans:
    a. For conventional loans, check the initial losses in 
NPV1t to evaluate whether there is any loss remaining. 
Loans with losses less than zero, where NPV1t  
0, will not receive any additional credit for seller/servicer 
recourse. For those loans, set RCtt = 0, and proceed to 
Step 6. Otherwise, if NPV1t > 0, go to Step 3.
    b. For FHA/VA loans, proceed to Step 5.
    3. Re-calculate initial loss severity rates using the full 
seller/servicer claim amount, PVSt, rather than the post-
insurance foreclosure cash flow, PV2t:
[GRAPHIC] [TIFF OMITTED] TP13AP99.108

[GRAPHIC] [TIFF OMITTED] TP13AP99.325

    4. Use NPV2t with appropriate percentage recourse 
(Type 2) coverage rates and survival factors to calculate seller/
servicer recourse coverage amounts, RCt:
[GRAPHIC] [TIFF OMITTED] TP13AP99.109

[GRAPHIC] [TIFF OMITTED] TP13AP99.326

    Go to Step 6.
    5. For FHA/VA loan groups, calculate the effective loss rate after 
recourse coverage amounts provided by VA guarantees:
[GRAPHIC] [TIFF OMITTED] TP13AP99.110

and then:
[GRAPHIC] [TIFF OMITTED] TP13AP99.377


[[Page 18260]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.327


    6. Calculate final loss severity rates separately for 
conventional and FHA/VA loans.
    a. For conventional loans, subtract the percent reduction in net 
losses provided by recourse coverage, RCt, from the 
initial loss severity rate, NPV1t:
[GRAPHIC] [TIFF OMITTED] TP13AP99.111

[GRAPHIC] [TIFF OMITTED] TP13AP99.328

    b. For FHA/VA loans, compute a weighted-average loss severity 
rate, using NPV1t--which includes FHA insurance--and 
NPVVAt--which includes VA insurance:
[GRAPHIC] [TIFF OMITTED] TP13AP99.378

[GRAPHIC] [TIFF OMITTED] TP13AP99.329

3.5.3.4 Output

    The resulting 120 monthly loss severity rates (NPV3t) 
for each loan group are used as inputs by the Cash Flow component of 
the stress test to calculate monthly (dollar) default losses (see 
section 3.9, Cash Flows, of this Appendix).

3.5.4 Multifamily Default and Prepayment

3.5.4.1 Overview

    The Multifamily Default and Prepayment component of the stress 
test calculates the monthly rates of default and prepayment for each 
multifamily loan group throughout the stress period. The process of 
computing default and prepayment rates requires input data on: one, 
loan group characteristics in the Enterprise portfolios at the 
beginning of the stress test; two, historical rent growth rate 
information to update values of collateral for the loans to the 
beginning of the stress test; and three the economic conditions of 
the stress period--interest rates, vacancy rates and rent growth 
rates. These input data are used to create values for the 
explanatory variables in the Multifamily Default and Prepayment 
component. The annual-equivalent default and prepayment rates for 
each month of the stress period are generated using the values of 
the explanatory variables and the regression coefficients (or 
weighting factors). These coefficients are based on statistical 
analysis of the relationship between default and prepayment rates 
and the explanatory variables. Finally, the annual-equivalent rates 
are converted into monthly rates for use in the Cash Flow component 
of the stress test to simulate loan terminations and associated 
credit losses.

3.5.4.2 Inputs

    Inputs for the Multifamily Default and Prepayment component of 
the stress test include loan group characteristics, interest rate 
series, historical rent indexes, and stress period rent growth rates 
and vacancy rates. Each of these are discussed below.

3.5.4.2.1 Loan Group Characteristics

    As described in section 3.1, Enterprise Data, of this Appendix, 
multifamily loan group characteristics data are generated through 
aggregation of individual Enterprise loans as of the beginning of 
the stress test, according to defined aggregation criteria. The 
characteristics of a loan group include both categorical and 
continuous variables. The values of categorical variables indicate 
the range within which a loan group characteristic falls (``value-
range''). The values of continuous variables are averages of the 
values of the characteristics of the underlying loans, where the 
weights are the unpaid principal balances of each loan in the group, 
at the start of the stress test. The following are loan group 
characteristics used in the Multifamily Default and Prepayment 
component of the stress test (using allowable values for each 
variable found in section 3.1, Enterprise Data, of this Appendix):
     Origination year
     Census region
     Metropolitan statistical area
     Product type
     Mortgage program
     Original LTV (the variable ``LTV0'' in 
equations below)
     Original coupon (the variable ``rc,0'' in 
equations below)
     Starting coupon (the variable ``rc,s'' in 
equations below)
     Starting UPB (the variable ``UPBs'' in 
equations below)
     Debt coverage ratio, at the time of purchase by the 
Enterprises (the variable ``DCR0'' in equations below)
     Amortization term, in months (the variable 
``Ta'' in equations below)
     Mortgage age, in months (at the start of the stress 
period; the variable ``As'' in equations below)

3.5.4.2.2  Interest Rate Series

    Three interest rate series are used in the Multifamily Default 
and Prepayment component. These series are generated from the 
Interest Rate component of the stress test, for each month of the 
stress period (see section 3.3, Interest Rates, of this Appendix). 
Historical values for one of these interest rate series are also 
required. (See below. Note that all interest rate series are in 
decimal format.) The particular input series are:
     Federal Home Loan Bank 11th District Cost of Funds 
Index (COFI) (the variable ``rb,t'' in equations below)
     Conventional mortgage rate (the variable 
``rf'' in equations below)
     Ten-year Constant Maturity Treasury Yield (the variable 
``y120t'' in equations below). Historical values of this 
variable are input starting 30 years prior to the start of the

[[Page 18261]]

stress test, and stress test simulation values are used to extend 
the series throughout the stress period.

3.5.4.2.3  Historical Rent Indexes

    Updating property values of collateral for multifamily loans at 
the beginning of the stress test requires use of rent indexes. The 
stress test uses the residential rent component of the Consumer 
Price Index (CPI), which is available from the U.S. Department of 
Labor, Bureau of Labor Statistics (BLS). The series required for 
this part of the stress test are those for the U.S., the four Census 
regions, and the 29 Metropolitan Statistical Areas (MSAs) covered by 
the BLS surveys.

3.5.4.2.4  Stress Period Vacancy Rates and Rent Growth Rates

    Monthly vacancy rate and rent growth rate series for the stress 
period are generated by the Property Valuation component of the 
stress test (see section 3.4, Property Valuation, of this Appendix). 
These series are used to update multifamily property values 
throughout the stress period.

3.5.4.3  Procedures

    [a] Separate default equations are used to distinguish between 
loans acquired through: one, cash purchases and two, negotiated 
transaction. In a cash purchase, an Enterprise acquires a newly 
originated loan that meets standard underwriting guidelines; the 
purchase can include recourse to the seller/servicer. In a 
negotiated transaction, an Enterprise generally acquires a pool of 
seasoned, nonconforming loans.
    [b] FHA-insured loans are a subset of loans that are purchased 
through negotiated transactions, but they are included with the cash 
transaction loans for default calculation purposes.
    [c] Fixed-rate multifamily loans have prepayment restrictions, 
for example, yield maintenance fees and lockouts, that severely 
limit prepayments for about two-thirds of the loan term. To account 
for the differences in prepayment speeds that result from these 
restrictions, five prepayment equations are used for the following 
types of loans: fixed-rate loans in the restriction period, fixed-
rate balloon loans beyond the restriction period, self-amortizing 
fixed-rate loans beyond the restriction period, balloon loans at the 
balloon point, and adjustable rate mortgages.
    [d] To calculate default and prepayment rates in the stress 
text, the input data described above are used to compute the values 
of explanatory variables for the equations for multifamily default 
and prepayment rates. A total of 16 explanatory variables (shown in 
Table 3-20) are computed for each loan group, and for each month of 
the stress period. The following describes calculations of 
explanatory variables and the resulting default and prepayment 
rates. Unless otherwise indicated, each variable subscripted with a 
``t'' is computed for the 120 months of the stress period. To 
illustrate each procedure, formulas are shown for one loan group for 
each month of the stress test. The same logic applies to all loan 
groups.
    [e] The values of explanatory variables in each month are used 
in the default and prepayment equations to calculate annual default 
and prepayment rates. The stress test computes default and 
prepayment rates that would result if the conditions prevailing in 
each month were to continue for an entire year. These annual rates 
are converted to monthly rates for use in section 3.9, Cash Flows, 
of this Appendix.

3.5.4.3.1  Computation of Explanatory Variables

3.5.4.3.1.1   Mortgage Age (At, AYt)

    [a] Mortgage age in each month of the stress period is 
calculated as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.113

[GRAPHIC] [TIFF OMITTED] TP13AP99.330

    [b] Since mortgage age enters the default and prepayment 
equations in years, rather than in months, an age-in-years variable, 
AYt, is created:
[GRAPHIC] [TIFF OMITTED] TP13AP99.114

3.5.4.3.1.2  Program Restructuring (PR)

    The stress test differentiates between cash programs in effect 
before 1988 for Fannie Mae and before 1992 for Freddie Mac 
(``original programs'') and later cash programs. This 
differentiation accounts for the greater credit risk of the earlier 
cash programs. The variable PR is used in two ways to adjust 
original program loan groups for this greater risk. PR is only used 
for loans in the cash programs (except FHA-insured loans) because 
OFHEO has identified the program structure deficiencies that caused 
this greater risk only on these loans. The variable is not used to 
adjust the risk profile of loans acquired through negotiated 
programs. The PR variable is computed for each loan group according 
to the following:
[GRAPHIC] [TIFF OMITTED] TP13AP99.115

First, PR is used as a categorical variable to distinguish the 
original cash programs from more recent cash programs of the 
Enterprises (``current programs''). This usage of PR captures the 
higher default risk of the Enterprises' original programs. Second, 
PR is used as a flag for when to adjust DCR0 and 
LTV0 for overly optimistic appraisal practices inherent 
in original cash program loans. (See sections 3.5.4.3.3.10, Formula 
for Constructing the DCR Time Series and 3.5.4.3.4.4, Construct the 
LTV Time Series, of this Appendix.)

3.5.4.3.1.3  Value of Depreciation Write-off (DW)

    The present value of tax benefits afforded to an investor/owner 
in a multifamily property is captured in a depreciation write-off 
variable (DW). Based on depreciation rules and OFHEO's estimates of 
the marginal tax rate for ordinary income, the marginal tax rate for 
capital gains, and the risk-adjusted return for multifamily 
projects, a value of 9.27 for this variable (DW) is used in the 
stress test. This value represents a 9.27 percent estimated return 
for a 20-year holding period on investments in multifamily property 
resulting from tax benefits associated with ownership and taxes paid 
on the ultimate sale of the property, based on 1995 data. OFHEO may 
change the value for this variable if there are significant changes 
in depreciation rules or tax rates. DW affects defaults and is held 
constant for

[[Page 18262]]

all cash programs throughout the stress period. However, it is not 
used to project default rates of negotiated programs.

3.5.4.3.1.4  Seller/Servicer Repurchase Flags (RF, RA)

    [a] Mortgage default in the stress test is defined as a loan 
termination in which the borrower must relinquish title to the 
property because of an inability to make loan payments. However, 
there is one exception for multifamily mortgages in certain 
negotiated programs. In these negotiated programs, when a loan 
becomes 90 days delinquent, the seller/servicer must buy the loan 
out of the pool and attempt to resolve the delinquency. For these 
loans, the stress test defines default as a 90-day delinquency, 
rather than a full default. The occurrence of 90-day delinquencies 
is always higher than the occurrence of full defaults, since many 
90-day delinquent loans cure or are modified.
    [b] To distinguish a ``90-day delinquency'' type of default from 
a full default, the stress test includes two categorical variables 
that flag fixed-rate (RF) and adjustable rate (RA) negotiated 
program loans with repurchase requirements:
[GRAPHIC] [TIFF OMITTED] TP13AP99.116

3.5.4.3.1.5  Joint Probability of Negative Equity and Negative Cash 
Flow (JPt)

    The joint probability of negative equity and negative cash flow 
(JPt) is defined as the probability that any given loan 
will simultaneously experience a loan-to-value ratio 
(LTVt) greater than 1.00 and a debt coverage ratio 
(DCRt) less than 1.00. JPt is the principal 
variable used in the stress test to measure the value of default to 
multifamily borrowers. Creating this variable involves updating 
DCRt and LTVt over time using a property net 
operating income (NOI) growth factor, changes in mortgage payments, 
loan amortization, and a capitalization rate multiplier. The NOI 
growth factor is updated over time using vacancy rate changes and 
rental inflation since loan origination. The capitalization rate 
multiplier is updated based on changes in interest rates since loan 
origination.

3.5.4.3.2  Updating Average Property Income

3.5.4.3.2.1  Create Rent Indexes for the Start of the Stress Period

    Rent indexes at the start of the stress period are created using 
time series of annual percent changes in the residential rent 
component of the CPI for each of the four Census regions and the 29 
MSAs covered by BLS surveys. If the stress test begins at a time 
other than January 1 (first quarter of the year), the residential 
rent component of the CPI at the end of the quarter just preceding 
the start of the stress test is used to create the final ``year'' of 
the rent index time series. Most MSA level CPI series produced by 
BLS start in 1970, but some do not begin until the 1980s. The 
regional CPI series are available beginning in 1978, so percent 
changes for these can only be computed starting in 1979. Each 
regional and MSA percent-change series is constructed as follows:
    1. Fill-in the pre-1979 regional series with percent changes in 
the rent index values for the national CPI, going back 30 years from 
the start of the stress test. If any MSA is missing one or more 
years of data, fill-in missing values from regional series. This 
results in 33 time series of annual rent growth rates for 30 years, 
ending in the year and quarter just preceding the beginning of the 
stress test.
    2. Using these time series, create the rent index value for each 
loan group at the start of the stress period, as a cumulative index 
from the loan origination year to the start of the stress test:
[GRAPHIC] [TIFF OMITTED] TP13AP99.117


[[Page 18263]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.331


    3. In order to link the rental series to loan group 
characteristics, first match each loan group by MSA code to the 
available residential rent series from BLS. If there is a match, 
then use that MSA series of historical annual growth rates of 
residential rent, as described above, to generate the value for 
Im,y. If the loan group is not in an MSA covered by the 
BLS residential rent series, then match the Census region of the 
property to the appropriate regional residential rent series, and 
use the regional historical annual growth rates of the residential 
rent series to generate the value for Im,y. Assume that 
all loans originate in the middle of the year, for purposes of the 
first-year rent growth rate. To accomplish this, the above formula 
uses the square root of the growth rate in the year of loan 
origination.

3.5.4.3.2.2  Update Each Rent Index throughout Stress Period

    The rent index at the beginning of the stress test 
(Im,y) is updated, for each loan group, throughout the 
stress period based on the following equation:
[GRAPHIC] [TIFF OMITTED] TP13AP99.118

[GRAPHIC] [TIFF OMITTED] TP13AP99.332

3.5.4.3.2.3  Create a Property Net Income Multiplier

    [a] The rent index series just created is combined with the 
vacancy rate series (Vt) provided by the Property 
Valuation component of the stress test to create a formula for 
updating the average, underlying, NOI in each month of the stress 
period. The following formula provides a multiplication factor that 
gives the ratio of current property NOI to NOI at loan origination 
(for cash programs), or at acquisition (for negotiated programs):
[GRAPHIC] [TIFF OMITTED] TP13AP99.119

[GRAPHIC] [TIFF OMITTED] TP13AP99.333


[[Page 18264]]


    [b] There are two constants in the above equation. The first, 
2.15, is the percentage decline in NOI due to a one percent increase 
in the vacancy rate. The second, 0.0623, is the average vacancy rate 
observed for multifamily rental properties in 1983-95. The average 
vacancy rate is used to approximate the vacancy rate of each loan at 
the time of origination (cash programs) or acquisition (negotiated 
programs). Nt measures how changes in rental inflation 
and vacancy rates together translate into percentage changes in net 
operating income since loan origination.

3.5.4.3.3  Create a DCR Time Series

    [a] DCR is the ratio of the property NOI to the mortgage 
payment. DCR at loan origination or acquisition (DCR0) is 
a loan characteristic input to the stress test. It is updated over 
time using the formula for Nt, and by updating the 
mortgage payment, if and when applicable. The mortgage payment 
changes regularly for ARMs. The stress test also changes mortgage 
payments for balloon loans that do not pay off at maturity. For such 
loans, the coupon interest rate is changed to the prevailing market 
rate at the time of balloon maturity. DCR0 for loans 
purchased under original cash programs (when PR=1) of the 
Enterprises are adjusted to make them consistent with current cash 
programs (current measurement practices) by multiplying them by 
0.8655.\12\ This adjusts for differences in appraisal practices 
between original and current cash programs.
---------------------------------------------------------------------------

    \12\ For Fannie Mae, these are cash loans purchased prior to 
1988. For Freddie Mac, these are cash loans purchased prior to 1992.
---------------------------------------------------------------------------

    [b] In addition, because UPB is decremented over time, according 
to the coupon rate and amortization term for each loan group, 
updates to UPB are required to update payments on ARM and balloon 
loans at maturity. Updates to UPB are also used to create current 
LTVs. Procedures for creating a time series of LTV ratios follows 
this discussion involving DCR construction. In the following 
procedures, both UPB and mortgage payments (PMT) are factors based 
on an original loan balance of one dollar and do not represent 
actual dollar amounts.

3.5.4.3.3.1  Create the Original Payment Factor for All Loans

    The original payment factor is based on original loan terms:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.120
    
    [GRAPHIC] [TIFF OMITTED] TP13AP99.334
    
3.5.4.3.3.2  Create Time Series of UPB Values for Fixed-rate, Fully 
Amortizing Loans

    For all fixed-rate, fully amortizing loans, create the UPB time 
series in the stress test period according to the following 
equation:
[GRAPHIC] [TIFF OMITTED] TP13AP99.121

3.5.4.3.3.3  Update Mortgage Payment Factors and UPB for ARMs and 
Balloon ARMs

    [a] Updating UPBt and PMTt for ARMs 
requires first creating the coupon interest rate series 
(rc,t) for each ARM loan group. This series will capture 
the effect of period and lifetime caps on the path of coupon rates.
    1. The current coupon rate at the start of the stress period, 
rc,s, is used for the mortgage coupon rates in the first 
12 months of the stress period rc,t:

rc,t = rc,s, for t = {1,...,12}

    2. In every twelfth month, compare:

rc,t >< (rb,t + 0.02375), for t = {12, 24, 
36,...108}
[GRAPHIC] [TIFF OMITTED] TP13AP99.335

    3. When, upon evaluation in step 2, rc,t < 
(rb,t + 0.02375), set:

rc,t+1...t+12 = min{(rb,t + 0.02375), 
(rc,t + 0.01), (rc,0 + 0.05)}

[[Page 18265]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.336


    4. When, upon evaluation in step 2, rc,t > 
(rb,t + 0.02375), set:

rc,t+1...t+12 = max{(rb,t + 0.02375), 
(rc,t-0.01), (rc,0-0.05)}
    5. When, upon evaluation in step 2, rc,t = 
(rb,t + 0.02375), set:

rc,t+1...t+12 = rc,t
    [b] The UPB percent at the start of the stress test is 
calculated using an original loan balance of one dollar, remaining 
term, and an average of the origination and starting coupons. The 
resulting UPB percent is used to calculate the payment factor in 
month one of the stress period:
[GRAPHIC] [TIFF OMITTED] TP13AP99.122

[GRAPHIC] [TIFF OMITTED] TP13AP99.123

[GRAPHIC] [TIFF OMITTED] TP13AP99.124

[GRAPHIC] [TIFF OMITTED] TP13AP99.125

[GRAPHIC] [TIFF OMITTED] TP13AP99.337

    [c] The time series of mortgage coupon rates (rc,t) 
from steps 1-5 is used to generate time series of payment factors 
and UPB percent factors for the remaining months of the stress 
period. These two series are developed simultaneously. In each 
month, each series is updated based on what happened in the other 
series in the previous month:
[GRAPHIC] [TIFF OMITTED] TP13AP99.126


[[Page 18266]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.127


[GRAPHIC] [TIFF OMITTED] TP13AP99.338

3.5.4.3.3.4  Create Payment and UPB Factors for Fixed-Rate Balloons

    Payment factors for balloon loans with fixed interest rates are 
held constant at PMT0 until the loans reach maturity. At 
maturity, the payment factor is updated to reflect current market 
interest rates, the remaining loan balance, and a new amortization 
term.\13\ Payment factors and UPB for balloon ARMs are constructed 
using the procedures just described for ARM loans, rather than the 
instructions for fixed-rate balloon loans.
---------------------------------------------------------------------------

    \13\ The remaining life of the loan is reset to equal the 
amortization term of the loan at origination.
---------------------------------------------------------------------------

    1. Set balloon term in months, Tm, according to 
product types listed in Table 3-18.
[GRAPHIC] [TIFF OMITTED] TP13AP99.270

    2. Create UPBt and PMTt throughout the 
stress period, according to when the balloon matures in the stress 
period. Loan group UPBs are reduced according to default and 
prepayment (balloon payoffs) rates (see section 3.5.4.3.6, 
Calculation of Default and Prepayment Rates, of this Appendix) in 
the balloon year, and for up to five years beyond the month of 
balloon maturity. Loan groups with balloon maturity prior to the 
start of the stress test are terminated after three years in the 
stress period (thirty-seventh month). Loan groups that mature during 
the stress test are terminated five years after maturity.
    a. If balloon term, Tm, is less than or equal to 
mortgage age at the start of the stress test, As, i.e., 
the loan has passed its balloon date or is just maturing when the 
stress test begins, then UPBt and PMTt are 
updated as follows:
[GRAPHIC] [TIFF OMITTED] TP13AP99.128

[GRAPHIC] [TIFF OMITTED] TP13AP99.129


[[Page 18267]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.130


[GRAPHIC] [TIFF OMITTED] TP13AP99.339

    b. If balloon term, Tm, is greater than mortgage age 
at start of stress test, As, then update UPBt 
and PMTt as follows.
[GRAPHIC] [TIFF OMITTED] TP13AP99.131

[GRAPHIC] [TIFF OMITTED] TP13AP99.132

[GRAPHIC] [TIFF OMITTED] TP13AP99.133

[GRAPHIC] [TIFF OMITTED] TP13AP99.134

[GRAPHIC] [TIFF OMITTED] TP13AP99.340

3.5.4.3.3.5  Formula for Constructing the DCR Time Series

    The formulas for updating DCR over time in the stress period are 
described below.
    1. For loans originated under current cash programs (where 
PR=0), and for all negotiated programs:
[GRAPHIC] [TIFF OMITTED] TP13AP99.135

    2. For loans originated under original cash programs, where 
PR=1:
[GRAPHIC] [TIFF OMITTED] TP13AP99.136


[[Page 18268]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.341



3.5.4.3.4  Create an LTV Time Series

    LTV is the ratio of the unpaid principal loan balance (UPB) to 
the value of the property. The UPB is updated over time as described 
above. The value of the property is adjusted based on the property 
net operating income multiplier (Nt) and a capitalization 
rate multiplier (described below). As with DCR, LTV must be adjusted 
for loans purchased under original Enterprise cash programs, to make 
them consistent with current cash programs.

3.5.4.3.4.1  Updating the Capitalization Rate Multiplier

    [a] The capitalization rate multiplier is the reciprocal of the 
capitalization rate and reflects what investors are willing to pay 
for an annual cash flow stream on a property, given the property and 
market conditions, as well as the opportunity cost of capital. LTV 
is updated in the stress test according to changes in the multiplier 
that result from changes in the opportunity cost of capital, as 
reflected through changes in market interest rates.
    [b] The capitalization rate multiplier is updated in two steps, 
based on changes in the ten-year CMT yield (a proxy for changes in 
the opportunity cost of capital).
    1. Compute the average monthly ten-year CMT yield for the loan 
origination-year:
[GRAPHIC] [TIFF OMITTED] TP13AP99.137

[GRAPHIC] [TIFF OMITTED] TP13AP99.342

    2. Compute the time series of ratios of capitalization rate 
multipliers based on the relative spread between the origination-
year ten-year CMT and each of the monthly values of the ten-year CMT 
throughout the stress period:
[GRAPHIC] [TIFF OMITTED] TP13AP99.138

[GRAPHIC] [TIFF OMITTED] TP13AP99.343

3.5.4.3.4.2  Construct the LTV Time Series

    [a] For loans acquired through current cash programs (where 
PR=0), or through negotiated programs:
[GRAPHIC] [TIFF OMITTED] TP13AP99.139

    [b] For loans acquired through original cash programs, where 
PR=1:
[GRAPHIC] [TIFF OMITTED] TP13AP99.140


[[Page 18269]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.344


    [c] For all loans, prevent LTVt from approaching zero by 
resetting small values to 0.01:
[GRAPHIC] [TIFF OMITTED] TP13AP99.141

3.5.4.3.5  Compute Joint Probability of Negative Equity and Negative 
Cash Flow

    [a] The values of the joint probability of negative equity and 
negative cash flow (JPt) are computed as the area under a 
bivariate standard normal density function. The form for this 
function is:
[GRAPHIC] [TIFF OMITTED] TP13AP99.142

[GRAPHIC] [TIFF OMITTED] TP13AP99.345

    [b] In the calculations of JPt, the two standard 
normal random variables (x and y) represent transformations of DCR 
and LTV values for individual properties. Standard normal random 
variables have normal (Gaussian) distributions, with a mean of zero 
and standard deviation of one. Any normally distributed random 
variable can be ``standardized'' by subtracting the mean from the 
variable, and then dividing by the standard deviation. In this 
application, the ``sample'' group for which the standard deviations 
apply could include all multifamily properties in the geographic 
location of the properties underlying the loan group being studied. 
Here the normally distributed variables are the true, but unknown ln 
(DCR) and ln (LTV) values for each loan, and their mean values are:
[GRAPHIC] [TIFF OMITTED] TP13AP99.143

[GRAPHIC] [TIFF OMITTED] TP13AP99.346

and
[GRAPHIC] [TIFF OMITTED] TP13AP99.144

    [c] The limits of integration (a and b) represent the distance 
between the logs of the at-risk boundaries for underlying 
properties--DCR=1.00 and LTV=1.00 and--Dt and 
Lt respectively. The joint probability variable is then 
the value of the bivariate density function, evaluated at particular 
values of the integration limits in each month of the stress period:

[[Page 18270]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.145


    [d] The following steps describe how to calculate the values of 
at and bt.
    1. First, compute the standard deviation of ln(DCRt) 
and ln (LTVt):
[GRAPHIC] [TIFF OMITTED] TP13AP99.146

[GRAPHIC] [TIFF OMITTED] TP13AP99.347

    2. The limits of integration in each month of the stress test, 
at and bt, are:
[GRAPHIC] [TIFF OMITTED] TP13AP99.147

[GRAPHIC] [TIFF OMITTED] TP13AP99.148

[GRAPHIC] [TIFF OMITTED] TP13AP99.348

    These equations reduce to:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.140
    
    [e] The coefficient of correlation between the logarithms of DCR 
and LTV is:  = -0.5975. It should be noted that standard 
software packages that compute bivariate normal probabilities do 
their integrations over the left tails of both (x and y) 
distributions. To estimate the left tail of the lnDCR and the right 
tail of the lnLTV distribution which is required to estimate 
JPt, one simply reverses the signs on the lnLTV 
integration limit (from b to -b) and the correlation coefficient 
(from -0.5975 to 0.5975).

3.5.4.3.5.1  Balloon Maturity Risk (BJPt)

    [a] The balloon year is defined as the 12 months leading up to 
and including the maturity month. Because of the contractual 
requirement to pay off a loan at maturity, a balloon loan with weak 
financials is more likely to default in the balloon year than at any 
previous time. The stress test captures this additional credit risk 
for balloon loans by giving extra weight to the JPt 
variable in the balloon year. This is accomplished by including a 
second JPt term in the default equations, which is only 
used for balloon loans, in the balloon year:
[GRAPHIC] [TIFF OMITTED] TP13AP99.150

[GRAPHIC] [TIFF OMITTED] TP13AP99.349

    [b] Not all loans will pay off or default by balloon maturity. 
For those that continue beyond balloon maturity, the stress test 
updates PMTt after the balloon date with current market 
interest rates (as described earlier) to simulate any increase (or 
decrease) in payments upon refinancing the property. This change in 
loan payments changes the default risk in the post-balloon period.

[[Page 18271]]

3.5.4.3.5.2  Relative Spread Variables (RSt, 
RSDt, RSUt)

    The incentive to prepay a mortgage because of the ability to 
refinance at lower interest rates is proxied by relative interest 
rate spreads. The difference here is that, for fixed-rate mortgages, 
the relative spread is split into two variables: one for when market 
rates are below the coupon rate (RSDt), and one for when 
market rates are above the coupon rate (RSUt). 
RSDt captures in-the-money prepayment options, and 
RSUt captures any dampening effect on cash-out 
refinancing when the prepayment option is out-of-the-money. For ARM 
loans, the relative spread variable (RSt) compares the 
current coupon rate to the current market rate on fixed-rate 
products.
    1. For each ARM loan group, compute the relative spread as:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.151
    
    2. For each fixed-rate loan group (including balloons), create 
the two spread variables:
[GRAPHIC] [TIFF OMITTED] TP13AP99.152

[GRAPHIC] [TIFF OMITTED] TP13AP99.153

3.5.4.3.5.3  Years-To-Go in the Yield-Maintenance Period 
(YTGt)

    [a] One feature common to most fixed-rate multifamily mortgages, 
whether balloon or fully amortizing, is the yield maintenance period 
(YMP). During a yield maintenance period, prepayment is restricted 
because borrowers cannot prepay the mortgage without incurring 
substantial penalties. For fixed-rate fully-amortizing mortgages, 
the YMP is 120 months. For fixed-rate balloon loans, the YMP 
averages two-thirds of the loan term, up to a maximum of 120 months. 
ARM loans do not have yield maintenance periods. Table 3-19, of this 
Appendix provides the term of the YMP for each loan product as 
follows:
[GRAPHIC] [TIFF OMITTED] TP13AP99.271

    [b] The YMP is used to create the explanatory variable years-to-
go (YTGt), which measures the number of years remaining 
in the yield maintenance period of the mortgage. This explanatory 
variable is a proxy for the size of prepayment penalties, which 
decline throughout the YMP:

[[Page 18272]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.154


    [c] YTGt has its maximum value in the first month of 
loan life, and declines to zero by the end of the YMP. For loan 
programs with lockouts, which prohibit prepayment for a stated time 
period, YTGt is set to ten for the duration of the 
lockout period.
[GRAPHIC] [TIFF OMITTED] TP13AP99.155

3.5.4.3.5.4  Relative Spread Variables in the Pre-balloon Period 
(RSD1t, RSD2t)

    For balloon loans during the post-yield-maintenance and pre-
balloon period, borrowers must decide whether to lock in a current 
interest rate or take their chances regarding what the market rate 
will be when the loan matures. To capture the additional incentive 
of borrowers to prepay in the two years prior to the balloon date, 
to take advantage of favorable interest rates when they exist, the 
stress test provides extra weight to the RSDt variable in 
both the year preceding the balloon year, and the year just prior to 
that:
[GRAPHIC] [TIFF OMITTED] TP13AP99.156

[GRAPHIC] [TIFF OMITTED] TP13AP99.157

[GRAPHIC] [TIFF OMITTED] TP13AP99.350

3.5.4.3.5.5  Market Rate for Fixed-Rate Mortgages (rf,t)

    The current market interest rate on fixed-rate single family 
mortgages is used to capture the effect of expectations of ARM 
borrowers with respect to future interest rate movements. This is in 
addition to the relative spread variable, RSt, used in 
the prepayment equation for ARM loans. While RSt measures 
differences between long-term and short-term interest rates, the 
long-term interest rate itself (rf,t) indicates the 
absolute level of interest rates.

3.5.4.3.5.6  Probability of Qualifying for Refinancing at Balloon 
Maturity (PQt)

    [a] When a balloon loan matures, the borrower is contractually 
required to pay off the outstanding UPB. To do this, the borrower 
generally obtains a new loan. In practice, payoff rates are 
dependent on the ability of the borrower and property to qualify for 
a new loan. For multifamily mortgages, the LTV must generally be 
less than or equal to 0.80, and the DCR must be greater than or 
equal to 1.20. The need for the property financials to meet 
origination underwriting criteria at the balloon date adds to 
extension risk, i.e., the risk that the loan will not pay off, but 
remain outstanding.
    [b] The stress test captures extension risk at the balloon date 
by estimating a separate payoff equation for balloon loans at or 
beyond maturity. The payoff equation includes only one variable, the 
probability of qualifying for refinancing (PQt). This is 
constructed like the joint probability of negative equity and 
negative cash flow variable (JPt), except that the limits 
of integration now reflect the minimal requirements for loan 
qualification rather than the boundary points for default. The 
integration limits are from t to +  
for lnDCRt (right tail) and from - to 
bt for lnLTVt (left tail), where:
[GRAPHIC] [TIFF OMITTED] TP13AP99.158


[[Page 18273]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.159


[GRAPHIC] [TIFF OMITTED] TP13AP99.351

    [c] The range of the integration limits is reversed from that 
used in calculating the JPt variable, because 
PQt is calculating the probability of financially strong 
loans, while JPt calculates the probability of 
financially weak loans. Again, in using a standard software package 
to calculate PQt, set the integration limit for 
t = -t and  = 
- because the package is set up to integrate left tails 
only.

3.5.4.3.5.7  Loan-to-Value Ratio (LTVt)

    The current loan-to-value ratio is used to capture the 
propensity of investors to initiate cash-out refinancing to increase 
borrowers' returns on equity. The time series of LTVt is 
used as an explanatory variable in prepayment equations.

3.5.4.3.5.8  Summary of All Explanatory Variables

    Table 3-20 outlines all of the explanatory variables that are 
used to calculate default and prepayment rates.

[[Page 18274]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.272



3.5.4.3.6  Calculation of Default and Prepayment Rates

    Conditional default and prepayment rates are calculated for each 
multifamily loan group based on the explanatory variables described 
above, and using statistical regression coefficients estimated on 
historical data. The regression coefficients provide weighting 
factors for each explanatory variable. The variables are each 
multiplied by their associated regression-coefficient (weights), and 
then added together to yield total weighting factors. Default and 
prepayment total weighting factors are combined in pairs to 
calculate the annual-equivalent conditional default and prepayment 
rates for each corresponding loan group in each month of the stress 
period. These annual-equivalent rates are then converted into 
monthly rates.

3.5.4.3.6.1  Combining Explanatory Variables into Total Weighting 
Factors

3.5.4.3.6.1.1  Default Weighting Factors (t)

    The calculation of the total weighting factors for defaults 
varies by loan program. Two total weighting factors are calculated 
for loan defaults. One calculation is for mortgages purchased 
through cash programs, and the other is for mortgages acquired 
through negotiated programs. For each loan

[[Page 18275]]

group, the appropriate formula is used for the entire stress period.
    For loan groups in cash programs:

t = -10.0191 + 1.2687 AYt-0.0790 
(AYt) \2\ + 0.6203 PR-0.0829 DW + 7.8230 JPt + 
2.6446 BJPt

    3. For loan groups in negotiated programs:

t = -9.6418 + 1.0596 AYt--0.0633 
(AYt) \2\ + 0.2627 RF + 0.6751 RA + 12.1660 
JPt + 2.6446 BJPt

3.5.4.3.6.1.2  Prepayment Weighting Factors (t )

    Prepayment total weighting factors are calculated using 
equations that differ both by product type and life-cycle stage. For 
any one loan group, one, two, or three different equations may be 
used during the stress period. Figure 3-4 illustrates how the 
prepayment weighting factor equations are used over the life of any 
particular loan group. Each block represents one of the five 
different equations for computing the prepayment total weighting 
factors.
[GRAPHIC] [TIFF OMITTED] TP13AP99.375

    1. Fixed-rate Mortgages (Fully Amortizing and Balloon Loans)

If the loan product is a ``fixed-rate'' or a non-ARM balloon, and 
for t where

YMP  At,
[GRAPHIC] [TIFF OMITTED] TP13AP99.160

    2. Fully-amortizing loans, out of yield maintenance

    If the loan product type is ``fixed-rate,'' and for t where

YMP < At:
[GRAPHIC] [TIFF OMITTED] TP13AP99.161

    3. Balloon loans out of yield maintenance, but prior to 
maturity.
    When the mortgage product is a balloon with a fixed interest 
rate, and for values of t where YMP < At and t < (m-11):

[[Page 18276]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.162


[GRAPHIC] [TIFF OMITTED] TP13AP99.352

    4. Fully-amortizing ARMs, and balloon ARMs before maturity.
    When the mortgage product is a fully-amortizing ARM, or a 
balloon ARM where t < (m-11), then:
[GRAPHIC] [TIFF OMITTED] TP13AP99.163

[GRAPHIC] [TIFF OMITTED] TP13AP99.353

    5. All balloon loans, on and after the maturity date.
    When the mortgage product is a balloon (ARM or fixed-rate), then 
the total weighting factors are calculated as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.164

[GRAPHIC] [TIFF OMITTED] TP13AP99.354

    Balloon loans do not all terminate at the balloon date. The 
stress test allows them to run-off according to default and 
prepayment (payoff) rate calculations, in the balloon year, and for 
up to five years beyond the balloon date. All balloon loans that do 
not terminate within five years beyond the balloon date are 
terminated in the sixty-first month. Loan groups with balloon dates 
prior to the start of the stress test (m < 0) are terminated in the 
thirty-seventh month of the stress period.

3.5.4.3.6.1.3  Calculating Annual Equivalent Default and Prepayment 
Probabilities

    [a] Once the time series of default and prepayment total 
weighting factors are computed for each loan group, they are 
combined in multinomial logit equations to calculate the annual-
equivalent default and prepayment probabilities. These probabilities 
represent what would happen over the course of a year, were default 
and prepayment probabilities for a given month (t) to continue for 
an entire year.
    [b] The annual-equivalent default probability, ADt, 
in each month, t, is computed as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.165

and the annual-equivalent prepayment probability, APt, in 
each month (t) is computed as:
[GRAPHIC] [TIFF OMITTED] TP13AP99.166

3.5.4.3.6.1.4  Terminating Balloon Loans after Maturity

    At the final termination point, annual-equivalent probabilities 
of default and payoff are calculated as functions of two 
explanatory-variable probabilities: the joint probability of 
negative equity and negative cash flow (JPt), and the 
probability of qualifying for a refinancing (PQt):

[[Page 18277]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.167


[GRAPHIC] [TIFF OMITTED] TP13AP99.355

3.5.4.3.7  Calculating Monthly Default and Prepayment Rates The 
monthly conditional default and prepayment rates are derived from 
the annual-equivalent probabilities for each month using geometric 
means. For default rates:
[GRAPHIC] [TIFF OMITTED] TP13AP99.168

and for prepayment rates:
[GRAPHIC] [TIFF OMITTED] TP13AP99.169

3.5.4.4  Output

    The 120 monthly default and 120 monthly prepayment rates are 
generated for each loan group and are used by the Cash Flow 
component of the stress test to compute monthly dollar amounts of 
loans that prepay and default (see section 3.9, Cash Flows, of this 
Appendix).

3.5.5  Multifamily Loss Severity

3.5.5.1  Overview

    Loss severity is the net cost to an Enterprise of a loan 
default. The loss severity rate is expressed as a percentage of the 
UPB at time of default. The stress test calculates loss severity 
rates for each multifamily loan group for each month of the stress 
period. Loss severity rates are discounted to calculate an effective 
loss rate in the month of default, adjusting various cost and 
revenue components of loss severity that occur following the default 
date. The effective loss severity rate is multiplied by the 
corresponding mortgage default rate to calculate the loan group 
loss-rate. The loss-rate is multiplied by the UPB in each month to 
compute the dollar amount of credit losses for each loan group.

3.5.5.2  Inputs

    [a] The following loan group characteristics are used:
     Program type
     Portfolio
     Net yield (the variable ``ry'' in equations 
below) \14\
---------------------------------------------------------------------------

    \14\ Net yield at the start of the stress test is used 
throughout the stress period for all loan groups, including ARMs.
---------------------------------------------------------------------------

     Passthrough rate (the variable ``rp'' in 
equations below) \15\
---------------------------------------------------------------------------

    \15\ Passthrough rate at the start of the stress test is used 
throughout the stress period for all loan groups, including ARMs.
---------------------------------------------------------------------------

    [b] The six-month Federal agency cost of funds (variable 
``rd,t'') interest rate series is used for discounting 
default-related cash flows in loss severity calculations. This 
series is an output from section 3.3, Interest Rates, of this 
Appendix.

3.5.5.3  Procedures

    The loss severity rates are calculated by program type and 
portfolio. Cash flows are discounted semi-annually. The impact of 
credit enhancements on cash programs with recourse and FHA-insured 
loan programs is calculated below. Credit enhancements for other 
multifamily program types are applied in section 3.9, Cash Flows, of 
this Appendix.

3.5.5.3.1 Retained Portfolio: Cash Programs Without Recourse

    [a] The basic loss severity equation is for loan groups 
consisting of retained loans purchased under cash programs without 
recourse. For these loan groups, loss severity rates are calculated 
as the UPB at the time of default (represented by the ``1'' in the 
following equation), plus the present value of foreclosure costs and 
property operating expenses, minus the net proceeds from sale of the 
property:
[GRAPHIC] [TIFF OMITTED] TP13AP99.170


[[Page 18278]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.356


    [b] Each NPVt value represents the loss severity rate 
for loans defaulting in month t of the stress period. The timing of 
events (e.g., time from default to foreclosure, etc.) used in the 
equation shown above is also used in the loss severity rate 
equations for all other program types and portfolios. The net 
operating loss on foreclosed properties for the 13 months that the 
property would be real estate owned (REO) is expensed in the seventh 
month of the 13-month holding period.

3.5.5.3.2 Sold Portfolio: Programs Without Recourse or Repurchase

    There is a slight change in the basic loss severity equation 
shown above for sold loans purchased under cash programs without 
recourse, and for negotiated programs without repurchase. Four 
months of interest are passed through to investors before the loans 
are bought out of security pools for default resolution. The 
passthrough interest expense in the second term of the loss severity 
equation, below, is discounted for two months. This represents a 
midpoint of the period of interest expenditures. In addition, the 
UPB at time of default is a direct cash outlay, occurring four 
months after default. Therefore, the UPB at time of default is 
discounted because the stress test accounts for this payment in the 
month of default. Therefore, the following modified equation is 
applied to sold loans purchased under cash programs without 
recourse, and negotiated programs without repurchase:
[GRAPHIC] [TIFF OMITTED] TP13AP99.171

[GRAPHIC] [TIFF OMITTED] TP13AP99.357

3.5.5.3.3 Retained Portfolio: Cash Programs With Recourse

    When loans are purchased under cash programs with recourse, the 
seller/servicer shares any losses with the Enterprise. The stress 
test computes the amount of recourse and reduces the gross severity 
rate as described below.
    1. Compute two additional revenue elements: interest income paid 
by the seller/servicer to the Enterprise (II) and (additional) 
proceeds from the seller/servicer (SP) recourse.
    a. Calculate mortgage interest income, II, paid by the seller/
servicer during the time between default and foreclosure:
[GRAPHIC] [TIFF OMITTED] TP13AP99.172

[GRAPHIC] [TIFF OMITTED] TP13AP99.358

    b. Calculate proceeds from the seller/servicer recourse (SP).
     Calculate the seller/servicer share of loss, S, as a 
fraction of the UPB:
[GRAPHIC] [TIFF OMITTED] TP13AP99.173


[[Page 18279]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.359


     Reduce seller/servicer loss share (S) by the interest 
income it has already paid to the Enterprise (II). Thus, the final 
seller/servicer payment will be:
[GRAPHIC] [TIFF OMITTED] TP13AP99.174

    2. Calculate net present value loss severity rates for defaults 
in each month (t) by summing the discounted values of all cost and 
revenue elements:
[GRAPHIC] [TIFF OMITTED] TP13AP99.175

In this equation, interest income (II) is discounted from the mid-
point of the time between default and foreclosure, to reflect that 
interest payments are made monthly by the seller/servicer throughout 
this period. The seller/servicer's payment, or share of loss, is 
discounted from the foreclosure date. This is also a midpoint date, 
because seller/servicers pay the Enterprise some recourse amounts 
prior to foreclosure, and the rest of the recourse amount 
approximately two months after foreclosure.

3.5.5.3.4 Sold Portfolio: Cash Programs with Recourse

    The steps for computing loss severity rates for cash programs 
with recourse for sold loans purchased follow the steps outlined for 
similar programs for retained loans. The differences are that the 
UPB at time of default is discounted, and there is an added expense 
element, the interest passthrough expense (IE) of payments made by 
the Enterprise to security holders. The UPB at time of default is 
discounted because this amount is disbursed to security holders four 
months after the time of default. The interest expense is computed 
for four months and discounted for two months.
    1. Calculate four months of passthrough interest expense:
    [GRAPHIC] [TIFF OMITTED] TP13AP99.176
    
    [GRAPHIC] [TIFF OMITTED] TP13AP99.360
    
    2. Calculate the loss severity rate for defaults in each month, 
t, using IE and other components as described above:
[GRAPHIC] [TIFF OMITTED] TP13AP99.177

3.5.5.3.5  Sold Portfolio: Negotiated Programs with Repurchase

    In the case of default on negotiated programs with seller/
servicer repurchase provisions, the Enterprises' losses represent a 
combination of foreclosures and alternative resolutions. These 
alternatives are loan restructuring, note sales, pre-foreclosure 
property sales, or acceptance of deeds in-lieu-of foreclosure. 
Seller/servicers are responsible for all resolution processes, 
including all post-foreclosure property

[[Page 18280]]

management and disposition. The Enterprise pays the seller/servicer 
claim, C, that results from the default-resolution expenses. There 
is typically a recourse account established for this purpose. Thus:
[GRAPHIC] [TIFF OMITTED] TP13AP99.178

[GRAPHIC] [TIFF OMITTED] TP13AP99.361

In this equation, the discount time period for the single cost 
component is the expected time to foreclosure rather than time to 
final property sale, to reflect a balance of default-resolution 
types and associated time intervals before claims are filed with the 
Enterprise.

3.5.5.3.6  FHA-insured Programs

    Loss severities on FHA-insured mortgages are set to three 
percent to reflect the costs of assigning defaulted loans to HUD.

3.5.5.4  Output

    The 120 monthly loss severity rates for each loan group are used 
by the Cash Flow component of the stress test to calculate monthly 
amounts of credit losses, net of recourse offsets (see section 3.9, 
Cash Flows, of this Appendix).

3.6  Other Credit Factors

3.6.1  Overview

    The Other Credit Factors component of the stress test accounts 
for sources of credit risk other than the risk of default by 
mortgage borrowers. These sources of credit risk include the risk of 
default by credit enhancement and derivative counterparties, as well 
as the risk of default of corporate securities, municipal 
securities, and rated mortgage-related securities. The stress test 
classifies these sources of credit risk into four ratings categories 
(``AAA'', ``AA'', ``A'' and ``BBB'') based on public ratings 
information, and establishes credit loss factors appropriate to each 
of these categories that are applied during the stress period.

3.6.2  Input

    The stress test uses credit ratings issued by Standard & Poor's, 
Moody's, Duff & Phelps and Fitch as the basis to assign 
counterparties (except seller/servicers) and securities into one of 
the four rating categories. The stress test only uses Standard & 
Poor's and Moody's ratings for seller/servicers.

3.6.3  Procedures

3.6.3.1  Identifying Other Credit Factors

    The stress test first identifies all non-mortgage borrower 
sources of credit risk and associated financial instruments, and 
groups them into two major categories-counterparties and securities. 
Counterparties are mortgage insurers, pool insurers, seller/
servicers, and counterparties for derivative contracts. Securities 
include mortgage-related securities, such as mortgage revenue bonds 
(MRBs) and private label REMICs, and non-mortgage investments, such 
as corporate and municipal bonds and asset-backed securities (ABSs).

3.6.3.2  Classifying Rating Categories in the Stress Test

    [a] Public ratings of a counterparty or security determine the 
extent of associated credit losses during the stress period. Based 
on these ratings, the stress test classifies counterparties and 
rated securities into one of the four rating categories:
     AAA--all securities/counterparties rated between AAA/
Aaa and AAA-/Aaa3
     AA--all securities/counterparties rated AA+/Aa1 and AA-
/Aa3
     A--all securities/counterparties rated A+/A1 and A-/A3
     BBB--all securities/counterparties rated BBB+/Baa1 and 
below (Unrated corporate securities and counterparties are included 
in the BBB category.)
    [b] For loans with more than one layer of mortgage credit 
enhancement coverage, only the ratings of the counterparty providing 
the primary layer of coverage are used. If the security or the 
primary coverage provider has different ratings from different 
rating agencies, i.e., a ``split rating,'' then the lower rating is 
used.

3.6.3.3  Accounting for Other Credit Factors

    [a] The stress test specifies the final haircuts (i.e., the full 
amount of discount for other sources of credit risk in the stress 
period) by rating categories as shown in Table 3-21. The stress test 
further specifies that haircuts increase by equal amounts in each 
month until the final haircut is reached during the 120th month of 
the stress period.
[GRAPHIC] [TIFF OMITTED] TP13AP99.273

    [b] Haircuts for each credit rating category in each month of 
the stress period can be obtained from the following formula:
[GRAPHIC] [TIFF OMITTED] TP13AP99.179


[[Page 18281]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.362


    [c] The haircut is applied to the cash flows of a rated security 
or payments due from a counterparty according to the following 
formula:
[GRAPHIC] [TIFF OMITTED] TP13AP99.180

[GRAPHIC] [TIFF OMITTED] TP13AP99.363

3.6.4  Output
    The outputs of the Other Credit Factors component are the stress 
period final haircuts by rating category and by counterparty and 
security category. These haircuts are inputs to section 3.7, 
Mortgage Credit Enhancements; section 3.5.3, Single Family Loss 
Severity; section 3.5.5, Multifamily Loss Severity; and section 3.9, 
Cash Flows, of this Appendix.

3.7  Mortgage Credit Enhancements

3.7.1  Overview

    For each loan group and each month of the stress period, the 
stress test calculates reductions to mortgage credit losses that 
reflect the effects of credit enhancements. This component 
calculates the values of eight loan group characteristics relating 
to credit enhancements, which are part of the Enterprises' starting 
position loan group characteristics, as described in Table 3-2 of 
this Appendix. These characteristics, combined with counterparty 
``haircuts,'' are used in section 3.5.3, Single Family Loss Severity 
and section 3.5.5, Multifamily Loss Severity, of this Appendix to 
calculate loss severity rates, and in section 3.9, Cash Flows, of 
this Appendix to calculate dollar reductions to credit losses.

3.7.2  Inputs

    This component uses the inputs listed in section 3.7.2.1, 
3.7.2.2, and 3.7.2.3 of this Appendix.

3.7.2.1  Enterprise Data on Mortgage Credit Enhancements

    [a] Loan-level information on mortgage credit enhancements:
     Type of mortgage credit enhancement
     Starting UPB
     Private mortgage insurance (PMI) percent coverage, if 
applicable
    [b] Contract-level information on mortgage credit enhancements, 
if applicable:
     Limited recourse coverage remaining
     Limited indemnification coverage remaining
     Starting account balance of spread accounts
     Starting account balance of collateral accounts
     Starting account balance of cash accounts
     Pool insurance coverage remaining
     Coverage expiration date, unless coverage has expired 
before the beginning of the stress period

3.7.2.2  Public Rating Information

    Rating information from four public rating agencies--Standard & 
Poor's, Moody's, Duff & Phelps and Fitch--is used for mortgage 
insurers and pool insurers, and Standard & Poor's and Moody's rating 
information is used for seller/servicers. A ``BBB'' rating category 
is attributed to unrated counterparties. For loans with more than 
one layer of credit enhancement coverage, only the ratings of the 
counterparty providing the primary layer of coverage are used. If 
the primary coverage provider has different ratings from different 
rating agencies, i.e., a ``split rating,'' then the lower rating is 
used. For each credit-enhanced loan, the following information is 
required where applicable:
     Public ratings of mortgage insurer
     Public ratings of pool insurer
     Public ratings of the seller/servicer

3.7.2.3  Counterparty Coverage Reduction Information

    Counterparty coverage reduction data (haircuts) obtained from 
section 3.6, Other Credit Factors, of this Appendix, are:
     Haircuts for each month of the stress period for 
counterparties in the ``AAA'' credit rating category
     Haircuts for each month of the stress period for 
counterparties in the ``AA'' credit rating category
     Haircuts for each month of the stress period for 
counterparties in the ``A'' credit rating category
     Haircuts for each month of the stress period for 
counterparties in the ``BBB'' credit rating category

3.7.3  Procedures

    Using the loan level and contract level information described 
above, the stress test first classifies the types of credit 
enhancement coverage within a loan group. Then it calculates values 
for the eight loan group characteristics relating to credit 
enhancements described in Table 3-2 of this Appendix. Of the eight 
characteristics, three are coverage amounts for the loan group for 
each of three types of credit enhancements, four are percentages of 
loan group UPB covered by each counterparty rating category, and one 
is the percentage of loan group UPB covered by dollar-denominated 
credit enhancements, as defined in section 3.7.3.1, Classification 
of Credit Enhancements, of this Appendix.

3.7.3.1  Classification of Credit Enhancements

    [a] The stress test separates all of the various mortgage credit 
enhancements into two categories--percent-denominated credit 
enhancements and dollar-denominated credit enhancements. Percent-
denominated credit enhancements cover losses based on the percentage 
of the loss incurred. This category includes private mortgage 
insurance (PMI), unlimited recourse, and unlimited indemnification. 
In addition to the percent-denominated credit enhancements listed 
here, certain multifamily programs have risk-sharing arrangements 
between the Enterprise and the seller/servicer. The process in the 
stress test that simulates the coverage of these programs is 
described completely in section 3.5.5, Multifamily Loss Severity, of 
this Appendix.
    [b] Depending on the specific credit enhancement type, the loss 
covered can be based on either the ``gross claim amount'' (which 
includes the defaulted principal balance, unpaid interest from 
default through

[[Page 18282]]

foreclosure, and associated expenses, but does not include the 
subsequent proceeds from the sale of REO), or the net loss incurred 
(which does include proceeds from the sale of REO). Specifically, 
private mortgage insurance coverage is based on the gross claim 
amount, while unlimited recourse and indemnification coverage are 
based on the net loss incurred. See section 3.5.3, Single Family 
Loss Severity, of this Appendix for details on how the coverage is 
applied. The stress test further classifies PMI as ``Credit 
Enhancement Coverage Type 1'' (Type 1), and unlimited recourse and 
unlimited indemnification as ``Credit Enhancement Coverage Type 2'' 
(Type 2).
    [c] Dollar-denominated credit enhancements cover losses on a 
dollar-for-dollar basis, up to a maximum amount (i.e., there is a 
``dollar cap'' on the coverage). This category includes limited 
recourse, limited indemnification, pool insurance, spread accounts, 
collateral posted under collateral pledge agreements, and cash 
accounts. The stress test classifies all the dollar-denominated 
coverages as ``Credit Enhancement Coverage Type 3'' (Type 3).

3.7.3.2  Calculating Percentage Coverage and Dollar Coverage Amounts:

    For each loan group, the stress test calculates the coverage for 
the overall loan group UPB provided by each type of credit 
enhancement (Types 1, 2, and 3) on the individual loans in the 
group.
    1. Credit Enhancement Coverage Type 1 is calculated as the UPB 
weighted average percent coverage for all the loans in the loan 
group with PMI coverage. Loans in the loan group that are not 
covered by PMI are assumed to have coverage of zero percent, for the 
purpose of calculating the weighted average. Thus if a loan group 
UPB is ten million dollars, and one million of that balance has 35 
percent Type 1 coverage, the overall loan group Type 1 coverage is 
3.5 percent.
    2. Credit Enhancement Coverage Type 2 is calculated as the UPB 
weighted average percent coverage for all the loans with unlimited 
recourse and unlimited indemnification coverage in the loan group. 
Because coverage is unlimited for each loan, the percent coverage at 
the loan level is 100 percent for covered loans. Loans in the loan 
group that are not covered by Type 2 credit enhancements are assumed 
to have coverage of zero percent, for the purpose of calculating the 
weighted average. Thus, if a loan group UPB is ten million dollars, 
and one million of that balance has 100 percent Type 2 coverage, the 
overall loan group Type 2 coverage is ten percent.
    3. To calculate the Credit Enhancement Coverage Type 3 (i.e., 
the total coverage of all dollar-denominated credit enhancements), 
the stress test first assigns each loan under a contract its pro-
rata share of the total dollar coverage for that contract (loans 
covered under a single contract may be assigned to several loan 
groups). The pro-rata dollar coverage of covered loans in a loan 
group is totaled to determine total dollar-denominated coverage for 
the entire group. This total dollar coverage is determined at the 
beginning of the stress period. Although the balances in spread 
accounts and collateral accounts at the beginning of the stress 
period could, in practice, fluctuate over time, the stress test 
specifies that these account balances are adjusted downward only to 
cover losses during the stress period, and are otherwise fixed.

3.7.3.3  Calculating Percent of UPB Covered by Each Counterparty Rating 
Category

    The stress test calculates the percent of loan group UPB covered 
by each of the four counterparty rating categories. The UPBs of 
loans with counterparties falling into each rating category are 
divided by the UPB of the loan group. The results are values for the 
following four loan group characteristics:
     Percent of UPB under AAA coverage
     Percent of UPB under AA coverage
     Percent of UPB under A coverage
     Percent of UPB under BBB coverage

3.7.3.4  Calculating the Percent of UPB Under Dollar-Denominated 
Coverage

    The stress test determines the percent of UPB under dollar-
denominated coverage for each loan group. This percentage is 
calculated by dividing the loan group UPB with Type 3 coverage by 
the total UPB amount of the loan group.

3.7.3.5  Calculating Coverage Against Credit Losses

    Based on loan group credit enhancement characteristics, the 
stress test simulates the coverage provided during the stress 
period. Percent-denominated and dollar-denominated mortgage credit 
enhancement coverages are calculated and applied separately and 
sequentially in the stress test to generate net credit losses for 
each loan group. The dollar coverage of percent-denominated credit 
enhancements for any loan group varies based upon the mortgage 
losses during the stress period for that group. Therefore, the 
effects of percent-denominated credit enhancements are determined in 
connection with the calculation of loss severity rates. By contrast, 
amounts of dollar-denominated credit enhancements (total dollar 
coverage amounts) are calculated as of the start of the stress 
period and factored directly into the calculation of cash flows.

3.7.3.5.1  Calculating Percent-Denominated Credit Enhancements

    The percent coverage rates for Type 1 and Type 2 credit 
enhancements are input into section 3.5.3, Single Family Loss 
Severity and section 3.5.5, Multifamily Loss Severity, of this 
Appendix to determine loss severity. The Loss Severity component 
uses this information, together with counterparty haircuts from 
section 3.6, Other Credit Factors, of this Appendix, to derive loss 
severity rates. Thus, the effects of percent-denominated credit 
enhancements are incorporated into the calculations of loss severity 
rates. These loss severity rates are then input to section 3.9, Cash 
Flows, of this Appendix to generate the dollar amounts of credit 
losses.

3.7.3.5.2  Calculating Dollar-Denominated Credit Enhancements

    Reductions in credit losses resulting from dollar-denominated 
credit enhancements depend on the amount of dollar losses for a loan 
group and the remaining available dollar-denominated coverage in 
each month of the stress test. Reductions are applied in section 
3.9.1, Whole Loans, of this Appendix. The algorithm implementing 
these reductions is described below.
    1. In each month, use the time-and category-specific haircuts 
(HR,t) from section 3.6, Other Credit Factors, of this 
Appendix to calculate a weighted average haircut for the loan group 
(Ht). The weights used are the percentages of UPB that 
fall into each of the four counterparty rating categories for each 
loan group. The formula is as following:
[GRAPHIC] [TIFF OMITTED] TP13AP99.181

[GRAPHIC] [TIFF OMITTED] TP13AP99.364

    2. In each month of the stress test, calculate the loan group 
dollar losses that are eligible for dollar-denominated coverage:
[GRAPHIC] [TIFF OMITTED] TP13AP99.182


[[Page 18283]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.365


    3. For each loan group, compare the total dollar losses eligible 
for dollar-denominated coverage (TDLt) with the remaining 
dollar coverage for the loan group in month t of the stress period 
(C3t). If TDLtC3t, then 
reduce loan group credit losses by 
C3t(1-Ht). If 
TDLtt, then reduce loan group credit losses 
by TDLt(1-Ht).
    4. Update the remaining dollar-denominated coverage for the loan 
group in the following month (C3t+1) as the maximum 
between zero and the value of the remaining dollar-denominated 
coverage for the loan group in the current month minus the total 
dollar losses eligible for dollar-denominated coverage for the loan 
group in that month. The formula is as follows:
[GRAPHIC] [TIFF OMITTED] TP13AP99.183

[GRAPHIC] [TIFF OMITTED] TP13AP99.366

    5. After generating the remaining balance of the dollar-
denominated coverage in month t+1 of the stress test 
(C3t+1), then go to steps 2-4 again, to derive the 
reduction to credit losses for month t+1 of the stress test. This 
process continues for each month of the stress test until all the 
dollar-denominated coverage for the loan group is used up or until 
the stress test reaches its 120th month.

3.7.4 Output

    For each loan group for each month of the stress period, the 
Mortgage Credit Enhancements component of the stress test generates 
loss coverage rates for percentage-denominated credit enhancements, 
and dollar loss reductions for dollar-denominated credit 
enhancements. The percentage coverage rates are used in section 
3.5.3, Single Family Loss Severity and section 3.5.5, Multifamily 
Loss Severity, of this Appendix to calculate loss severity rates. 
Dollar loss reductions are used in section 3.9.1, Whole Loans, of 
this Appendix to adjust default losses.

3.8 Other Off-Balance Sheet Guarantees

3.8.1 Overview

    In addition to guaranteeing mortgage-backed securities they 
issue as part of their main business, the Enterprises guarantee 
other instruments, referred to as ``other off-balance-sheet (OBS) 
guarantees.'' The stress test does not explicitly project the 
performance of these other OBS guarantees. Instead, it addresses the 
capital requirement for other OBS guarantees by adding the product 
of the total other OBS guarantees principal balance and 45 basis 
points to the total amount of capital required to maintain positive 
total capital throughout the ten-year stress period.

3.8.2 Input

    [a] The OBS Guarantees component requires the Enterprise's 
outstanding balances for the following OBS guarantees at the 
beginning of the stress period:
     Tax-exempt multifamily housing bonds
     Single-family whole-loan REMICs
     Multifamily whole-loan REMICs
     Any other instruments or obligations that fit the 
definition of ``Other Off-Balance Sheet Obligations'' in 12 CFR 
1750.2
    [b] Any instruments or obligations, 100 percent of whose 
collateral is guaranteed by the Federal Housing Authority (FHA), are 
excluded from the total dollar amount of other OBS guarantees.

3.8.3 Procedures

    The OBS Guarantees component first calculates the total 
outstanding balance of all other OBS guarantees at the beginning of 
the stress period by summing the outstanding balances for tax-exempt 
multifamily housing bonds, single-family whole-loan REMICs, 
multifamily whole-loan REMICs, and any other instruments or 
obligations that fit the definition of other OBS guarantees. The 
dollar amount of capital required for other OBS guarantees is then 
computed as the total outstanding balance of all other OBS 
guarantees at the beginning of the stress period times 45 basis 
points.

3.8.4 Output

    The OBS Guarantees component produces one number: the dollar 
amount of capital required for other OBS guarantees. This number is 
input to the Calculation of the Risk-Based Capital Requirement 
component to compute the risk-based capital required for the 
Enterprises.

3.9 Cash Flows

3.9.1 Whole Loans

3.9.1.1 Overview

    [a] Both Enterprises hold single family and multifamily mortgage 
loans in their retained portfolios and guarantee passthrough 
mortgage-backed securities (MBS) owned by investors and backed by 
pools of such mortgage loans. Loans held in portfolio are referred 
to as ``retained loans,'' and loans backing guaranteed securities 
are referred to as ``sold loans.'' Together, retained loans and sold 
loans are referred to as ``whole loans.''
    [b] The Enterprises receive all principal and interest payments 
on their retained loans, except for a servicing fee--a portion of

[[Page 18284]]

the interest payment retained by the servicer as compensation. On 
sold loans, the Enterprises receive guarantee fees and earn float 
income. Float income is earned when the Enterprises invest principal 
and interest payments for sold loans for the period of time between 
the receipt of the payments and the remittance of the payments, net 
of guarantee fees, to security holders. The length of time an 
Enterprise can invest these payments depends on the security payment 
cycle (the remittance cycle).
    [c] The calculation of whole loan cash flows requires loan group 
information as the basic input data, as well as information on 
interest rates, mortgage performance and the credit quality of third 
party credit enhancements. Cash flows are produced for each month of 
the stress period for each loan group. (The stress test includes the 
dollar amount of credit losses in cash flows, even though such 
losses are not literally cash flows.)

3.9.1.2 Inputs

3.9.1.2.1 Loan Group Data

    The following data as of the start of the stress test are used 
for whole loan cash flow computations:
     Product type
     Starting unpaid principal balance
     Starting coupon
     Servicing fee
     Mortgage age
     Remaining term
     Guarantee fee (for sold loans)
     Remittance cycle (for sold loans)
     Passthrough rate (for sold loans)
     Original coupon (for ARMs)
     Margin (for ARMs)
     Amortization term (for balloons)

3.9.1.2.2 Interest Rates

    Whole loan cash flow calculations require the following interest 
rates for each of the 120 months of the stress period:
     One-, three-, and five-year Constant Maturity Treasury 
yields (CMT)
     11th District Federal Home Loan Bank Cost of Funds 
Index (COFI)
     Overnight Federal Funds rate (for calculation of float 
earnings)

3.9.1.2.3 Mortgage Performance Data

    Whole loan cash flow calculations also require the default, 
prepayment, and loss severity rates, which are computed as described 
in section 3.5, Mortgage Performance, of this Appendix, for each 
loan group for each month of the stress period.

3.9.1.3 Procedures

    This section describes calculations of prepaid principal, 
scheduled principal, UPB, interest, and float income for fully 
amortizing, monthly pay, fixed-rate loan groups. It then describes 
the adaptation of these calculations for biweekly, adjustable-rate, 
and balloon loans. Lastly, this section describes calculations of 
the dollar amount of credit losses.

3.9.1.3.1 Fully Amortizing, Monthly Pay Fixed-Rate Loans

    [a] The calculations discussed for fully amortizing, monthly 
pay, fixed-rate loans apply not only to loan groups made up of 30-
year and 15-year loans, but also to loan groups comprised of second 
lien, step, tiered payment mortgage (TPM), and graduated payment 
mortgage (GPM) loans.
    [b] Scheduled principal and interest payments for fully 
amortizing monthly pay, fixed-rate loans are computed using standard 
equations based on three variables: UPB, starting coupon, and 
remaining term.
    [c] The stress test computes the amounts of prepaid principal 
and defaulted principal in each month by multiplying the loan 
group's UPB at the end of the previous month by the prepayment and 
default rates for that loan group for that month. The stress test 
computes amounts of scheduled principal (the principal that is not 
defaulted principal nor prepaid principal) in each month by 
multiplying the scheduled monthly principal (principal computed 
according to an amortization schedule) by one minus the sum of the 
monthly prepayment and default rates.
    [d] The stress test computes the current loan group UPB for the 
end of a month by subtracting the amount of scheduled principal, 
prepaid principal, and defaulted principal in the month from the UPB 
at the end of the previous month.
    [e] To compute monthly interest remitted to an Enterprise for 
retained loan groups, the stress test multiplies the loan group net 
yield (current coupon less servicing fee) by the UPB at the end of 
the previous month less the current month's defaulted principal. To 
compute monthly guarantee fees for sold loan groups, the stress test 
multiplies the monthly guarantee fee by the UPB at the end of the 
previous month less the current month's defaulted principal.
    [f] To compute float income earned by an Enterprise on monthly 
principal and interest payments received from servicers and later 
remitted to security holders, the stress test multiplies scheduled 
principal and interest and prepaid principal by the Federal Funds 
rate for a number of days appropriate to the remittance cycle of the 
associated MBS. The stress test calculates float for three 
remittance cycles. Depending on the remittance cycle, prepaid 
principal may or may not be held for the same number of days as 
scheduled principal and interest.
    1. If an Enterprise holds scheduled principal and interest and 
prepaid principal for seven days before remittance to the security 
holder, float is calculated by multiplying the sum of scheduled 
principal and interest and prepaid principal, by the Federal Funds 
rate times seven divided by 365. (The Federal Funds rate is an 
annual rate. Multiplying the rate by this fraction produces the 
float income for the seven days that the Enterprise has the 
mortgagor's payment). The Enterprise earns float income on the full 
scheduled interest payment, because even if a mortgagor prepays a 
mortgage before the end of a month, remitting less than a full 
month's interest on the prepaid principal, the servicer must forward 
the interest for the rest of the month to the Enterprise. The 
Enterprise remits a full month's interest to the security investor.
    2. If an Enterprise remits scheduled principal and interest to 
the investor three days prior to receiving it from the servicer, but 
holds prepaid principal 38 days before remittance to the security 
holder, servicers are not required to forward to the Enterprise any 
prepayment-related shortfall in monthly interest, so the Enterprise 
must make up the short fall in interest to the security holder 
caused by a mortgagor's prepayment. If the prepayment is made in the 
first part of a month, the Enterprise owes the security holder 
interest at the security passthrough rate for the balance of the 
month. If the prepayment is made in the second half of the month, 
the Enterprise owes the security holder interest at the security 
passthrough rate for the balance of the current month and all of the 
following month. This is an average of 30 days of interest at the 
security passthrough rate on mortgagor prepayments. The float amount 
for this remittance cycle consists of:
     scheduled monthly principal and interest due the 
Enterprise multiplied by the Federal Funds rate times minus 3, 
divided by 365, plus
     prepaid principal multiplied by the Federal Funds rate 
times 38, divided by 365, minus
     prepaid principal multiplied by the passthrough rate 
(current coupon less the servicing fee less the guarantee fee) times 
30, divided by 360
    3. If an Enterprise holds scheduled principal and interest for 
57 days prior to remittance to the security holder and holds prepaid 
principal for 68 days prior to remittance to the security holder, 
the Enterprise owes the security holder an average of 30 days of 
interest at the security passthrough rate on mortgagor prepayments. 
The float amount for this remittance cycle consists of:
     scheduled monthly principal and interest due the 
Enterprise multiplied by the Federal Funds rate times 57, divided by 
365, plus
     prepaid principal multiplied by the Federal Funds rate 
times 68, divided by 365, minus
     prepaid principal multiplied by the passthrough rate 
(current coupon less the servicing fee less the guarantee fee) times 
30, divided by 360

3.9.1.3.2  Biweekly Loans

    While most mortgages require monthly payments, biweekly 
mortgages require payments every two weeks. The cash flow 
calculations described above for monthly pay, fully amortizing 
fixed-rate loans apply, except that the relevant time interval is 
two weeks rather than one month. In addition, biweekly, rather than 
monthly default and prepayment rates are applied. The stress test 
then allocates the biweekly cash flows to the proper month. The 
first biweekly cash flow occurs 14 days into the stress period. 
Subsequent biweekly cash flows occur at 14 day intervals. All the 
cash flows occurring during the same calendar month are added 
together to arrive at the monthly cash flow.

3.9.1.3.3  Adjustable-Rate Loans

3.9.1.3.3.1  Single Family RMS

    (a) The current interest rate for an adjustable-rate mortgage 
(ARM) is adjusted based on an interest rate index and a margin. ARM 
loan groups are indexed to either the

[[Page 18285]]

one-or three-year CMT, or the COFI, as appropriate to their product 
types. The product type ``ARMs Other'' is indexed to the COFI index.
    (b) The mortgage age of the loan group is used to determine the 
initial month of the stress test in which to adjust the current 
interest rate. The loan group interest rate is adjusted then and 
every 12 months thereafter, regardless of the index.
    (c) The stress test calculates annual and lifetime maximum 
interest rates (ceilings) and minimum interest rates (floors). 
Annual maximum and minimum new interest rates for the adjustment 
period are calculated by adding or subtracting, respectively, two 
percent to, or two percent from, the current interest rate (current 
coupon). Lifetime maximum and minimum interest rates are calculated 
by adding or subtracting, respectively, five percent to, or five 
percent from, the original interest rate (original coupon). The 
minimum lifetime interest rate is at least three percent. The 
maximum lifetime interest rate is no more than 14 percent.
    (d) The stress test adds the margin to the appropriate ARM 
interest rate index value to get a prospective interest rate. If the 
prospective interest rate is greater than the maximum new interest 
rate, the stress test sets the interest rate to the maximum new 
interest rate. If the prospective interest rate is less than the 
minimum new interest rate, the stress test sets the interest rate to 
the minimum new interest rate. After these steps, the prospective 
interest rate (adjusted as appropriate) becomes the current interest 
rate. The computation continues as described above for fully 
amortizing monthly pay fixed-rate loans groups.

3.9.1.3.3.2  Multifamily ARMs

    (a) The interest rate for a multifamily ARM is indexed to the 
Federal Home Loan 11th District Costs of Funds (COFI). The 
computations are as described for single family ARMs except that: 
one, the rate is reset every month subject to 2 percent cap, 2 
percent floor, and 3 percent life rate minimum; and two, the 
borrower payment is reset every 12 months, subject to a payment cap 
limiting the payment change to no more than 7.5 percent of the 
previous period payment.
    (b) Resetting the multifamily ARM rate at a frequency different 
from the frequency by which the payment is reset and restricting 
increases in the borrower payment may result in a payment that is 
less than the amount necessary to fully amortize the UPB at the 
current ARM rate. In such situations, the shortfall is added to the 
outstanding balance. The maximum amount by which the UPB is allowed 
to increase (negatively amortize) is limited to 125 percent of the 
original UPB.

3.9.1.3.4  Balloon Loans

    Calculations of cash flows for balloon loans are the same as for 
fully amortizing monthly pay, fixed-rate loans, except the balloon 
loan matures before the principal is fully amortized. Upon maturity, 
all unpaid principal is due. Loans are amortized based on their 
amortization terms. The stress test computes the number of months 
remaining until the balloon payment by subtracting the loan group 
mortgage age from the loan group balloon period and adding one. The 
loan group balloon period is identified according to the value of 
the variable, Product Type. If the Product Type is Balloons-Other, 
the balloon period is ten years.

3.9.1.3.5  Credit Losses

    To compute the dollar amount of credit losses, the stress test 
multiplies the monthly defaulting principal for a loan group by the 
loss severity rate for that month and loan group. That loss severity 
rate takes into account percentage-based credit enhancements, as 
described in section 3.5.3, Single Family Loss Severity and section 
3.5.5, Multifamily Loss Severity, of this Appendix. The resulting 
loss amount is further reduced by amounts of available dollar-based 
credit enhancements, as described in section 3.7, Mortgage Credit 
Enhancements, of this Appendix.

3.9.1.4  Output

    Whole loan cash flows are inputs to the preparation of pro forma 
balance sheets and income statements for each month of the stress 
period. See section 3.10, Operations, Taxes, and Accounting, of this 
Appendix. For loan groups made up of retained loans, cash flows 
consist of 120 months of scheduled principal, prepaid principal, 
defaulted principal, credit losses, and interest.

3.9.2  Mortgage-Related Securities

3.9.2.1  Overview

    (a) Both Enterprises invest in various types of mortgage-related 
securities: single class MBS, multi-class derivative mortgage 
securities (Collateralized Mortgage Obligations, REMICs, and 
Strips), and mortgage revenue bonds (MRBs). Single class MBS and 
derivative mortgage securities may be issued by the Enterprises, by 
Ginnie Mae, or by private issuers. MRBs are issued by State and 
local governments or their instrumentalities. Certain asset-backed 
securities with housing-related collateral (manufactured housing 
loans) that are similar in their cash flow characteristics to 
mortgage derivatives are treated in the stress test as mortgage 
derivative securities.
    (b) The Enterprises receive principal and interest payments on 
these securities. Payments on single class MBS represent the 
passthrough from underlying pools of mortgages of all principal and 
interest payments, minus servicing and guarantee fees, on the 
underlying pools of mortgages. Payments on derivative mortgage 
securities represent some of the cash flows produced by an 
underlying pool of mortgages and/or mortgage-related securities, 
determined according to rules set forth in public offering documents 
for the securities. Unlike MBS and derivative mortgage-related 
securities, mortgage revenue bonds have specific maturity schedules 
and call provisions; however, the collateral backing MRBs consists 
largely of mortgages or mortgage securities, and the pattern of 
principal payments is closely related to that of their underlying 
mortgage collateral. The stress test treats them in a manner similar 
to the treatment of single class MBS. A very small number of 
mortgage-related securities for which data are insufficient for the 
generation of precise cash flows (referred to as ``miscellaneous 
MRS'') are also treated in this manner. The category miscellaneous 
MRS includes a very small number of Enterprise and private label 
REMIC securities that are not modeled by a commercial information 
service.
    (c) In addition to reflecting the defaults of mortgage borrowers 
during the stress period, the stress test considers the effects of 
credit stress on securities that are rated by nationally recognized 
rating services, that is, mortgage revenue bonds and private-issue 
mortgage-related securities. Enterprise and Ginnie Mae securities 
are not rated, and the stress test reflects no credit losses on 
these securities. In the stress test, all rated securities 
experience increasing credit impairments throughout the stress 
period, which are reflected by reductions of contractual interest 
payments and losses of principal.
    (d) The calculation of cash flows for mortgage-related 
securities requires information from the Enterprises identifying 
their holdings, publicly available information characterizing the 
securities, interest rate information, mortgage performance 
information, and credit rating information for rated securities.
    (e) Cash flows-monthly amounts of principal payments, defaulted 
principal, and/or interest-are produced for each month of the stress 
period for each security (principal-and interest-only securities pay 
principal or interest). These cash flows are input to the 
Operations, Taxes, and Accounting component of the stress test.

3.9.2.2  Inputs

3.9.2.2.1  Securities

3.9.2.2.1.1  Single Class MBS Issued by the Enterprises and Ginnie Mae

    For the single class MBS issued by the Enterprises and Ginnie 
Mae and held by an Enterprise at the start of the stress test, the 
stress test requires information identifying the Enterprise's 
holdings and information describing the MBS and the underlying 
mortgage collateral.
    1. The following information is provided by the Enterprises:
     Pool number (identifying the security)
     Original principal balance (the original pool balance 
multiplied by the Enterprise's percentage ownership)
     Starting principal balance (the pool balance at the 
start of the stress period multiplied by the Enterprise's percentage 
ownership)
    2. Every month, the Enterprises make public through securities 
data services updated information about the MBS they issue. The 
stress test uses pool numbers for MBS held by an Enterprise to 
access the following information from these monthly data releases:
     Pool prefix (designates the product type of the MBS, 
for example, 30-year single family fixed-rate)
     Issue date
     Maturity date
     Security coupon
     Original pool balance
     Starting pool balance

[[Page 18286]]

     Weighted average maturity of the underlying loans at 
the time the security was issued
     Weighted average remaining maturity of the underlying 
loans at the start of the stress test
     Weighted average original coupon of the underlying 
loans at the time the MBS was issued
     Weighted average current coupon of the underlying loans 
at the start of the stress test
     Interest rate index (ARM MBS only)
     Weighted average interest rate margin for the 
underlying loans (ARM MBS only)
     Weighted average passthrough rate (the security coupon 
for some types of ARM MBS)

3.9.2.2.1.2  Derivative Mortgage Securities Issued by the Enterprises 
and Ginnie Mae

    [a] For the derivative mortgage securities issued by the 
Enterprises and Ginnie Mae that are held by an Enterprise at the 
start of the stress test, the stress test requires information 
identifying the Enterprise's holdings and information describing the 
underlying mortgage collateral. The Enterprises provide the 
following information:
     CUSIP number (unique security identifier assigned by 
the Committee on Uniform Security Identification Procedures)
     Original principal balance of the security (notional 
amount for interest-only securities) at the time of issuance, 
multiplied by the Enterprise's percentage ownership
     Starting principal balance, or notional amount, at the 
start of the stress period multiplied by the Enterprise's percentage 
ownership
    [b] The stress test requires information about the multi-class 
transactions of which these securities are a part, including 
information describing all component securities, the underlying 
collateral, and the rules directing cash flows to the component 
classes. This information is obtained from public sources, including 
public offering documents and public securities data services.
    [c] Obtaining sufficient information to calculate the cash flows 
of the underlying collateral may require multiple steps. For 
example, for a derivative mortgage security backed by single class 
MBS. Step 1, obtain, from public information, the pool numbers and 
principal balances for the specific underlying MBS. Step 2, consult 
public sources to obtain additional information as enumerated in 
section 3.9.2.2.1.1, for each of these MBS.

3.9.2.2.1.3  Mortgage Revenue Bonds and Miscellaneous MRS

    [a] The stress test requires two types of information for 
mortgage revenue bonds and miscellaneous MRS held by an Enterprise 
at the start of the stress test: one, information identifying the 
Enterprise's holdings and two, additional information about the 
securities. The following are obtained from the Enterprises to 
identify their holdings:
     CUSIP number
     Original principal balance
     Starting principal balance
    [b] The following additional information required for the stress 
test is available from public sources, including public offering 
documents and public securities data services:
     Issue date
     Maturity date
     Security interest rate
     Credit rating (for rated securities)

3.9.2.2.2  Interest Rates

    Interest rates projected through the stress period are necessary 
to calculate principal amortization and interest payments for ARM 
MBS and for derivative mortgage securities with indexed coupon 
rates. The stress test generates interest rates for each month of 
the stress period, as described in section 3.3, Interest Rates, of 
this Appendix.

3.9.2.2.3  Mortgage Performance

    The rate and pattern of principal payments of mortgage-related 
securities depend on the prepayments and, to a much smaller extent, 
the defaults of the underlying mortgage loans. Cash flow 
calculations require default and prepayment rates that are 
appropriate to the underlying mortgage collateral for each mortgage-
related security. Rates are generated as described in section 3.5.2, 
Single Family Default and Prepayment, and section 3.5.4, Multifamily 
Default and Prepayment, of this Appendix.

3.9.2.2.4  Third-Party Credit Exposure

    In calculating the principal and interest payments of mortgage-
related securities, the stress test treats defaults the same as 
prepayments. Thus, investors receive amounts of security principal 
equal to defaulted, prepaid, and scheduled principal on the 
underlying loans in the pool. For rated securities (e.g., mortgage 
revenue bonds and private-issue MRS), the risk of security default 
is reflected by reducing the calculated principal and interest 
payments for these instruments. These reductions, or haircuts, are 
described in section 3.6, Other Credit Factors, of this Appendix.

3.9.2.3  Procedures

    The sections below describe the calculations for single class 
MBS issued by the Enterprises and Ginnie Mae, the calculations for 
derivative mortgage securities, and calculations for MRBs and 
miscellaneous MRS.

3.9.2.3.1  Single Class MBS Issued by the Enterprises and Ginnie Mae

    [a] The calculation of cash flows for single class MBS issued by 
the Enterprises and Ginnie Mae follows the procedures outlined 
earlier in section 3.9.1, Whole Loans, of this Appendix. The 
collateral underlying each MBS is treated as one single family loan 
group. (For purposes of identifying appropriate default and 
prepayment rates for the small number of multifamily MBS held by the 
Enterprises, the stress test treats the underlying loans as 30-year 
fixed-rate single family mortgages.) Amounts of defaulted mortgage 
principal (reflecting the security guarantee) are advanced to 
security holders, and scheduled and prepaid mortgage principal are 
passed through to security holders. Interest is calculated at the 
security coupon rate (the weighted average passthrough rate for ARM 
MBS issued by the Enterprises). Security cash flows are calculated 
for the month in which mortgagor payments are made.
    [b] For each MBS, the stress test applies default and prepayment 
rates and computes the amortization of principal, based on the 
characteristics of the underlying loans. The stress test applies 
amortization and default and prepayment rates for sold loan groups 
(of the Enterprise that issued the MBS) that have characteristics 
consistent with the characteristics of the MBS collateral, with the 
following caveat. The stress test specifies that loans underlying an 
MBS reflect the national distribution of original LTV and Census 
divisions for all otherwise similar sold loans. Therefore, default 
and prepayment rates represent the weighted averages for loans 
groups in all LTV categories and Census divisions that are otherwise 
similar to the MBS collateral.
    [c] For Ginnie Mae MBS, the mortgage coupon for the underlying 
loan group equals the Ginnie Mae passthrough rate plus 0.5 percent. 
For fixed-rate Ginnie Mae MBS, the underlying loans are assumed to 
have the same distributions of LTVs and Census divisions as the 
Enterprise's sold portfolio FHA and VA loans with the same coupon 
and origination year. For loans underlying Ginnie Mae ARM MBS, the 
stress test uses default and prepayment rates for otherwise similar 
conventional ARM loans in the sold portfolio.
    [d] For ARM MBS, interest rate and monthly payment adjustments 
for the underlying loans are calculated in the same manner as they 
are for ARM loan groups, except that for Ginnie Mae ARM MBS, there 
is a one percent annual rate cap.
    [e] For balloon and biweekly MBS, cash flows for the underlying 
loans are calculated in the same manner as they are for balloon loan 
groups; product type information, such as the length of the balloon 
period, is determined by the MBS pool prefix and the MBS maturity 
date.
    [f] For purposes of calculating cash flows, the stress test 
treats GPMs, TPMs, GEMs, and Step mortgages that back MBS as 30-year 
fixed-rate mortgages.

3.9.2.3.2  REMICs and Strips

    [a] Cash flows for derivative mortgage securities are generated 
according to standard securities industry procedures, in five steps.
    1. Determine the percentage Enterprise ownership of a particular 
security by dividing the portion of the original principal balance 
or notional amount held by the Enterprise by the total original 
principal balance or notional amount of the derivative mortgage 
security.
    2. Identify the characteristics of the underlying collateral of 
the derivative mortgage security.
    3. Calculate the cash flows for the underlying collateral in the 
manner described for whole loans and MBS above, based on stress test 
interest, default, and prepayment rates.
    4. Calculate all cash flows for the derivative mortgage security 
classes by applying the rules stated in public offering materials.
    5. Determine the cash flows attributable to the specific 
securities held by an Enterprise, applying the Enterprise's 
ownership percentage.

[[Page 18287]]

    [b] The stress test uses a commercial information service for 
steps 2 through 5. The stress test models mortgages using a limited 
set of loan product types and ARM indexes. The information service 
accurately models a larger set of mortgage product types and all ARM 
indexes supplied by the interest rate component of the stress test 
(see section 3.3, Interest Rates, of this Appendix).

3.9.2.3.3  Mortgage Revenue Bonds and Miscellaneous MRS

    [a] Cash flows for mortgage revenue bonds and miscellaneous MRS 
are computed in the same manner as for single class MBS, using the 
approach described above. The stress test uses default and 
prepayment rates for single family, fixed-rate FHA and VA loans with 
coupons that are 75 basis points higher than the security coupon, 
and with the LTV and Census division distributions that are similar 
in all other respects to sold FHA or VA loans of the Enterprise that 
holds the security. The stress test uses a 30-year original maturity 
of the underlying loans, and loan age is computed based on the date 
when the security was issued. Monthly interest is calculated at the 
bond coupon for the amortizing balance.
    [b] Principal and interest payments are then reduced by applying 
the haircuts specified in section 3.6, Other Credit Factors, of this 
Appendix.

3.9.2.4  Outputs

    Amounts of principal, interest, and, in the case of rated 
securities, defaulted principal, are produced for each security. 
These outputs are used as inputs to the Operations, Taxes, and 
Accounting component, which prepares pro forma financial statements. 
See section 3.10, Operations, Taxes, and Accounting, of this 
Appendix.

3.9.3  Debt and Related Cash Flows

3.9.3.1  Overview

    [a] The Debt and Related Cash Flows component of the stress test 
produces cash flows for debt, guaranteed investment contracts 
(GICs), preferred stock, debt-linked derivative contracts, and 
mortgage-linked derivative contracts.\16\ Although mortgage-linked 
derivative contracts are usually linked to assets rather than 
liabilities, they are treated similarly to debt-linked derivative 
contracts and, therefore, are covered in this section of the 
Appendix. The Enterprises issue debt to fund their asset portfolios. 
Preferred stock issued by the Enterprises performs two functions: it 
funds asset portfolios and serves as capital. The Enterprises enter 
into derivative contracts for three reasons: to reduce the interest 
rate risk of specific securities (micro hedge); to hedge the overall 
interest rate risk of their business (macro hedge); or to create a 
synthetic liability (combination of a security and a derivative 
contract) with a lower net cost than the equivalent actual security.
---------------------------------------------------------------------------

    \16\ The notional balance of a mortgage-linked derivative 
contract declines based on the declining balance of a reference 
mortgage pool.
---------------------------------------------------------------------------

    [b] The Debt and Related Cash Flows component produces 
instrument level cash flows for the ten years of the stress test. 
Debt and preferred stock cash flows include interest (or dividends 
for preferred stock) and principal payments (or redemptions for 
preferred stock), while debt-linked and mortgage-linked derivative 
contract cash flows are composed of interest payments and receipts. 
(Throughout the remainder of section 3.9.3, references to ``interest 
payments'' include interest received, as well as interest paid, on 
debt-linked and mortgage-linked derivative contracts. ``Principal 
payments'' refers to payments of principal on debt and redemptions 
of preferred stock.) Debt and preferred stock are categorized in one 
of the three classes listed and described in Table 3-22.
[GRAPHIC] [TIFF OMITTED] TP13AP99.274

    [c] Debt-linked derivative contracts consist of interest rate 
caps, floors, and swaps. The primary difference between debt and 
debt-linked derivative contracts, in terms of calculating cash 
flows, is that interest payments on debt are based on principal 
amounts that are eventually repaid to creditors, whereas on debt-
linked derivative contracts interest payments are based on notional 
amounts that never change hands. Table 3-23 describes the six 
classes of debt-linked derivative contracts.

[[Page 18288]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.275


    [d] Mortgage-linked swaps are similar to debt-linked swaps 
except that, for the former, the notional balance amortizes based on 
the performance of certain MBS pools. The two classes of mortgage-
linked derivative contracts are listed and described in Table 3-24.
[GRAPHIC] [TIFF OMITTED] TP13AP99.276

3.9.3.2  Inputs

    [a] The Debt and Related Cash Flows component of the stress test 
requires numerous inputs. Many of the instrument classes require 
simulated interest rates because their interest payments adjust 
periodically based on rates tied to various indices. These rates are 
generated as described in section 3.3, Interest Rates, of this 
Appendix. Instrument level inputs provided by the Enterprises are 
listed in the Table 3-25.

[[Page 18289]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.277



[[Page 18290]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.278


    [b] In addition to the above inputs, the mortgage-linked 
derivative contract cash flows require inputs for the performance of 
linked mortgage assets, including default and prepayment rates from 
the single family default and prepayment component of the stress 
test (See section 3.5.2, Single Family Default and Prepayment, of 
this Appendix) and periodic and lifetime minimum and maximum coupons 
for ARM MBS. Mortgage-linked derivative contract identification 
numbers are used to link the derivative contract to pool information 
on specific MBS. This link allows retrieval of pool information that 
will be used to determine how the notional balance of the swap 
amortizes, including the coupon rate, issue date, maturity date, 
weighted average coupon (WAC), and weighted average maturity (WAM) 
for each pool.

3.9.3.3  Procedures

    [a] The debt and related cash flow component calculates separate 
cash flow streams for principal and interest payments. The stress 
test performs the following steps: determines the timing of cash 
flows; calculates a principal or notional factor; obtains the coupon 
or dividend factor; projects principal cash flows or changes in the 
notional amount; and projects interest cash flows.
    [b] Projected cash flows for callable or cancelable instruments 
may be altered by implementing a call decision rule for debt or a 
cancellation decision rule for swaps. In addition, special cases 
exist where instruments have complex characteristics, thereby 
requiring additional processing to compute cash flows. Each of these 
steps is described below.
    1. The first step requires determining the timing of cash flows 
or the payment dates. The three inputs that are required to 
accomplish this task are maturity date, payment frequency, and the 
previous payment date. Payment frequency, defined as the number of 
payments per year, takes on one of five values depending on how 
often coupon payments are made. These values are given in Table 3-
26.
[GRAPHIC] [TIFF OMITTED] TP13AP99.279

    2. Payment dates are based on the last payment date and the 
payment frequency until the instrument matures. For example, if the 
stress test is run on an Enterprise's data as of June 30, 1998, then 
an instrument with a previous payment date of April 15, 1998, that 
matures on October 15, 1999, and has quarterly payments will require 
payments on July 15, 1998, October 15, 1998, January 15, 1999, and 
so forth until maturity or, in the case of preferred stock, 
throughout the stress test. In the stress test, payments are 
allocated to specific months, not specific days within the month.
    3. The second step requires the calculation of a principal 
factor. The principal factor is defined as a percentage of original 
value of the instrument. In most instances, where there is no 
amortization of principal, the principal factor is one for each 
payment date until the stated maturity date, when it converts to 
zero. For debt and debt-linked derivative contracts that amortize, 
either a principal or a notional amortization schedule is provided 
by the Enterprises, or the amortization schedule is obtained from 
the offering materials for public securities. In the case of 
mortgage-linked derivative contracts, notional balances are 
amortized in the manner described in section 3.9.2, Mortgage-Related 
Securities, of this Appendix for principal balances of mortgage-
backed securities held by an Enterprise. A GIC is a liability that 
may amortize; however, an amortization schedule may not be 
available. When amortization information is unavailable, the issue 
amount of the GIC is assumed to be paid on the maturity date of the 
instrument. The remaining term is used to determine maturity dates 
for GICs.
    4. The third step requires the calculation of a coupon or 
dividend factor. The coupon or dividend factor is an adjustment 
factor used to calculate the portion of the annual coupon or 
dividend rate applicable to a given period. It depends on day count 
conventions used to calculate the accrued interest for the 
instrument and is determined using one of the three calculations in 
Table 3-27.

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[GRAPHIC] [TIFF OMITTED] TP13AP99.280


    5. The fourth step in the process involves calculating principal 
cash flow. Principal payments can be classified as either principal 
payments on zero coupon bonds or principal payments on all other 
instruments. All principal payments are paid at maturity for zero 
coupon bonds, and the principal amount is equal to the face amount 
of the bond. For all non-zero coupon bond instruments, principal 
outstanding for the current period is determined by multiplying the 
issue amount by the principal factor for the current period. The 
principal payment equals the amount of principal outstanding at the 
end of the current period less the principal outstanding at the end 
of the previous period, or zero if the instrument has a notional 
balance.
    6. The fifth step involves calculating interest and dividend 
cashflows. Instruments can be classified into six generic categories 
based on their interest payment characteristics. These are fixed-
rate instruments, zero coupon bonds, discount notes, floating-rate 
instruments, interest rate caps and floors, and swaps. Interest or 
dividend cash flows for an instrument in a period are calculated as 
the product of the principal/notional amount of the instrument for 
the given period, the coupon or dividend rate, and the coupon or 
dividend factor.
    [c] To determine the interest or dividend payments for fixed-
rate instruments, the current period principal amount is multiplied 
by the product of the coupon or dividend rate and current period 
coupon or dividend factor. Interest payments for zero coupon bonds 
and discount notes are equal to zero. For discount notes, if the 
amounts for original discounts are not provided, they are estimated 
as the product of unpaid balance, yield, and number of days between 
issue and maturity dates divided by 360.
    [d] Interest payments on floating-rate instruments (except for 
floating-rate preferred stock, which is discussed later in this 
section) are calculated as principal balance multiplied by the 
coupon for the current period. The current period coupon is 
calculated by adding a spread to the appropriate interest rate index 
and multiplying by the coupon factor. The coupon for the current 
period is set to this amount as long as the rate lies between the 
lifetime maximum and minimum rates, as periodic maximum and minimum 
rates are not recognized. Otherwise the coupon is set to the maximum 
or minimum rate.
    [e] Caps and floors are derivative instruments that pay or 
receive interest only if their specified index is above the strike 
price for caps and below it for floors. Interest payments on caps 
and floors are determined similarly to those for the debt 
instruments above; however, payments are based on notional amounts 
instead of principal amounts. The appropriate projected interest 
rate index is compared to the instrument's cap or floor rate (strike 
price). Interest payments are either paid or received depending on 
whether the Enterprise is in a long or short position in a cap or a 
floor. If a cap is purchased and the strike price is less than the 
rate on the cap's interest rate index, then the interest payment on 
the cap is the index less the cap rate multiplied by the notional 
amount of the cap. If a floor is purchased and the floor rate is 
higher than the index, then the interest payment on a floor is equal 
to the floor rate minus the index rate multiplied by the notional 
balance of the floor. Otherwise interest payments are zero for caps 
and floors.
    [f] A swap is a derivative contract that requires counterparties 
to exchange periodic interest payments. Swaps are modeled as two 
separate instruments, consisting of a pay side and a receive side, 
with interest payments based on the same notional balance but 
different interest rates. For debt-linked swaps, interest payments 
are determined using the criteria of fixed-rate or floating-rate 
instruments as described above.
    [g] For the pay side of mortgage-linked swaps, the component 
calculates the reduction in the notional balance due to scheduled 
monthly principal payments (taking into account both lifetime and 
reset period caps and floors), prepayments, and defaults of the 
reference MBS pool. The notional balance of the swap for the 
previous period is reduced by this amount to determine the notional 
balance for the current period. Interest payments for a given period 
are calculated as the product of the notional balance of the swap in 
that period and the coupon rate applicable for that period.
    [h] For the receive side of mortgage-linked swaps, the component 
calculates cash flows in the same manner as debt and debt-linked 
derivative contracts. The only difference is that the notional 
balance of the swap is amortized based upon the monthly pay-downs 
for an underlying MBS pool, as described for the pay side above. For 
the receive side, interest amounts are cash inflows.
    [i] In order to reduce interest costs and/or deepen the market 
for their securities, the Enterprises may issue debt denominated in, 
or indexed to, foreign currencies, and eliminate the resulting 
foreign currency exposure by entering into currency swap agreements. 
When they hedge their foreign exposure in this manner, the component 
creates synthetic debt denominated in U.S. dollars and pays interest 
accordingly.
    [j] Some debt and debt-linked derivative contracts have call or 
cancellation features that allow an Enterprise to terminate them at 
certain points in time. Whether or not a call or cancellation will 
be exercised is evaluated for all debt and the debt-linked 
derivative contracts that require cash outflows. For example, only 
the pay side is evaluated for swaps. If the pay side is cancelled, 
then the receive side is cancelled at the same time. Callable 
instruments are treated in the following manner. First, project cash 
flows for the callable instrument assuming that the instrument is 
not callable. Second, for each payment period when the instrument 
can be called, equate the outstanding balance or notional amount of 
the security to the sum of the discounted values of the projected 
cash flows. The discount rate that makes these two amounts 
equivalent is called the yield-to-maturity.\17\ Third, convert the 
yield-to-maturity to a bond-equivalent yield and compare the bond-
equivalent yield to the projected Federal Agency Cost of Funds for 
debt with a comparable maturity. Because the stress test does not 
project Federal Agency Cost of Funds indexes for every possible 
maturity, a linear interpolation is performed between the next 
higher and lower maturities to estimate the cost of funds for those 
maturities that are not projected. Finally, if the Federal Agency 
Cost of Funds is lower than 50 basis points below the bond-
equivalent yield of the callable instrument, then the instrument is 
called. Otherwise, the instrument is not called, and it is evaluated 
for call at the next payment period.
---------------------------------------------------------------------------

    \17\ For instruments with notional balances, the yield-to-
maturity is equal to the instrument's coupon or interest rate.
---------------------------------------------------------------------------

    [k] Some instruments have complex or non-standard features, and 
cash flows cannot be computed using only the data listed earlier. 
Characteristics of these types of instruments include complex 
principal or notional amortization schedules, complex coupon reset 
formulas for floating-rate instruments, and European call options 
for callable instruments. In these instances, additional information 
is obtained to define a set of rules to reflect the complex features 
of debt and debt-linked derivative contracts, thereby permitting the 
accurate calculation of cash flows for these instruments.
    [l] An example of an instrument with complex features is an 
indexed amortizing swap. This instrument is not standard because its 
notional amount declines in a way that is dependent upon the level 
of interest rates. This type of swap is structured

[[Page 18292]]

with an amortization table that contains a notional balance 
reduction factor for a given range of interest rates. To compute 
cash flows for this instrument, the notional balance at each payment 
date must be calculated. While raw data provides the notional 
balance at the beginning of the stress period, the notional balance 
at each payment date during the stress period must be calculated.
    [m] Other instruments that require special treatment are 
currency linked notes, the redemption value of which is tied to a 
specific foreign exchange rate. They require special treatment 
because the stress test does not forecast foreign currency rates. If 
these instruments are hedged, then they become part of synthetic 
debt created in conjunction with a swap as discussed previously. If 
these instruments are not hedged, the following treatment applies. 
In the up-rate scenario, the U.S. Dollar per unit of foreign 
currency ratio is increased in proportion to the increase in the 
ten-year CMT. For example, if the ten-year CMT shifts up by 50 
percent, then the U.S. Dollar per unit of foreign currency ratio 
shifts up by 50 percent. In the down-rate scenario, the foreign 
currency per U.S. Dollar ratio is decreased in proportion to the 
decrease in the ten-year CMT. The redemption value of these 
instruments may also have minimum and maximum principal amounts, 
which also must be taken into consideration in determining cash 
flows.
    [n] As the final step in the process, the interest cash flows 
for debt-linked and mortgage-linked derivative contracts are 
``haircut'' (i.e., reduced) by some percentage to account for the 
risk of counterparty insolvency. The percentage haircut used is 
based on the public rating of the counterparty, and the year during 
the stress period in which the cash flow occurs (Refer to section 
3.6, Other Credit Factors, of this Appendix for details on how the 
haircuts are applied.) The cash flows are all added together (pay 
side and receive side) for all contracts with a given 
counterparty.\18\ The haircut is applied to the net cash owed by the 
counterparty in a given month. If the Enterprise owes the 
counterparty money, then no haircut is applied.
---------------------------------------------------------------------------

    \18\ Cash flows are not aggregated together with a given 
counterparty for currency swaps. Instead, haircuts are applied to 
each individual currency swap.
---------------------------------------------------------------------------

    [o] Because the stress test does not forecast foreign exchange 
rates, the counterparty haircut percentages are applied to the pay 
side of currency swaps, instead of the receive side, to ``gross up'' 
the payment. Therefore, when synthetic debt is created, the effect 
is to increase the cost of the synthetic debt equal to the haircut 
amount.

3.9.3.4  Output

    Output consists of cash flows for debt, preferred stock, and 
derivative contracts. Cash flows include monthly interest and 
principal payments for debt, dividends and redemptions for preferred 
stock, and interest payments for debt-linked and mortgage-linked 
derivative contracts.

3.9.4  Non-Mortgage Investment and Investment-Linked Derivative 
Contract Cash Flows

3.9.4.1  Overview

    [a] The Enterprises primarily invest in non-mortgage assets as a 
source of liquidity. They also enter into investment-linked 
derivative contracts to reduce the interest rate risk of specific 
securities (micro hedge), hedge the overall interest rate risk of 
their business (macro hedge), or create a synthetic asset 
(combination of a security and a derivative contract) with a higher 
net yield than the equivalent actual security.
    [b] The stress test calculates the cash flows for these assets 
at the instrument level. The cash flows consist of interest payments 
and receipts and principal payments for the ten years of the stress 
test. (Throughout the remainder of section 3.9.4, references to 
interest payments include interest received on investment-linked 
derivatives products.) Compared to the treatment of debt and related 
cash flows, the stress test takes a more simplified approach to 
modeling non-mortgage instruments (including linked derivative 
contracts) held by the Enterprises. Rather than determining the 
specific payment frequencies of each instrument, the stress test 
assumes standardized payment frequencies by types of instruments. 
For this purpose, the stress test distinguishes among six classes of 
securities and eight classes of derivative contracts. Table 3-28 
lists and defines the six classes of securities.
[GRAPHIC] [TIFF OMITTED] TP13AP99.281

    [c] Table 3-29 defines the seven classes of derivative contracts 
and provides a description of what is included in each. (An eighth 
class, mortgage-related derivatives, is covered in section 3.9.3, 
Debt and Related Cash Flows, of this Appendix.)

[[Page 18293]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.282


    [d] Stress test procedures are divided into two distinct steps: 
one, establishing interest payment dates; and two, calculating the 
instrument level cash flows based on payment criteria and instrument 
characteristics.

3.9.4.2  Inputs

    [a] The stress test requires instrument and interest rate inputs 
for the calculation of interest payments and receipts and principal 
payments. Instrument level inputs provided by the Enterprises are:
     Issue date
     Face/notional amount
     Maturity date
     Coupon rate
     Index
     Spread
     Instrument I.D. to link pay and receive sides of swaps
     Pay/receipt code
     Payment frequency
     Cap rate
     Cap strike price
     Counterparty identification, if applicable
     Public rating(s) of instrument or counterparty
    [b] Each instrument class (security or derivative contract) uses 
only those inputs relevant to that instrument class.
    [c] In addition to the inputs provided by the Enterprises, this 
component requires projections for the stress period for a number of 
interest rates. The calculation of all of these interest rates is 
described in section 3.3, Interest Rates, of this Appendix. Ten 
classes of instruments are linked to various interest rates. These 
interest rates are required as inputs in order to adjust 
periodically the interest payments on the respective instruments. 
The particular interest rate used is based on the instrument's 
specifications. The available interest rates are listed in Table 3-
30.
[GRAPHIC] [TIFF OMITTED] TP13AP99.283


[[Page 18294]]



3.9.4.3  Procedures

    [a] One of seven interest payment calculations is assigned to 
each instrument class. These are a semi-annual fixed rate of 
interest, quarterly fixed and floating rates of interest, monthly 
fixed and floating rates of interest, a fixed rate of interest due 
at maturity based on the number of days an instrument is 
outstanding, and a monthly floating rate of interest based on the 
difference between an interest rate index and a strike price. Table 
3-31 indicates the type of payment calculation for each of the 
various instrument classes.
[GRAPHIC] [TIFF OMITTED] TP13AP99.284

    [b] The first step in processing the data is establishing the 
interest payment dates. Asset-backed securities (ABSs), amortizing 
swaps, and caps require monthly interest payments. For all other 
instrument classes, the interest payment dates are determined by 
working backward from the maturity date, using the payment 
assumptions for each instrument class. For example, if the maturity 
date is September 15, 1999, for an instrument that pays interest 
semi-annually, then interest payment dates are September 15, 1999, 
March 15, 1999, etc. until the initial payment date within the 
stress period is determined. Payments made in the stress period are 
allocated to specific months, not specific days within the month.
    [c] The second step is the calculation of instrument level cash 
flows based on payment criteria and instrument characteristics. 
Interest payment dates are based on the criteria established above. 
For the non-derivative instrument classes except for ABS, each 
interest payment is based on the face amount of the security. ABS 
interest payments are based on the remaining principal balance of 
the instrument after adjusting for prepayments. The entire amount of 
principal is due at maturity, except in the case of ABS, where the 
face amount is reduced by principal prepayments. Interest and 
principal payments for securities are, therefore, based on the 
formulas in Table 3-32.

[[Page 18295]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.285


[GRAPHIC] [TIFF OMITTED] TP13AP99.367

    [d] For derivative contracts such as swaps and caps, interest 
payments are calculated using notional amounts instead of principal 
balances. The stress test treats swaps as two separate instruments, 
consisting of a pay side and a receive side, using the criteria of 
fixed-rate or floating-rate instruments as described above. Each 
interest payment is based on the original notional amount of the 
derivative contract except for amortizing swaps, which have interest 
payments based on the remaining notional balance after adjusting for 
prepayments. Prepayment speeds for amortizing swaps are set equal to 
the prepayment speeds for floating-rate ABSs.
    [e] Caps can be purchased, in which case an Enterprise receives 
interest, or sold, in which case an Enterprise pays interest. 
Interest payments on caps are determined in the following manner. If 
the strike price of the cap is less than or equal to the interest 
rate index, then interest payments are calculated based on the 
difference between the index and the strike price. If the strike 
price of the cap is greater than the interest rate index, then 
interest payments are zero. The formulas in Table 3-33 are used to 
calculate interest payments and receipts for investment-linked 
derivative contracts.

[[Page 18296]]

[GRAPHIC] [TIFF OMITTED] TP13AP99.286


    [f] Equations for calculating interest on derivative contracts 
use the same notation as equations for securities. In addition, the 
following notations are used:
     N = notional amount of the instrument
     K = strike price
    [g] Once the cash flows for interest and principal have been 
calculated for a particular investment or investment-linked 
derivative contract, the cash flow is ``haircut'' (i.e., reduced) by 
a specified percentage determined by the public rating of the 
investment or derivative counterparty and the year during the stress 
period in which the cash flow occurs, as described in section 3.6, 
Other Credit Factors, of this Appendix. The haircuts are applied to 
all investment cash flows at the instrument level. However, for 
investment-linked derivative contracts, the cash flows are added 
together (pay side and receive side) for all contracts with a given 
counterparty. The haircut is applied to the net cash owed by the 
counterparty in that month. If the Enterprise owes the counterparty 
money, then no haircut is applied.

3.9.4.4  Output

    Interest and principal payments are produced for each instrument 
for the 120 months of the stress period. These cash flows are inputs 
to section 3.10, Operations, Taxes, and Accounting, of this 
Appendix.

3.10  Operations, Taxes, and Accounting

3.10.1  Overview

    This component describes the procedures for creating pro forma 
balance sheets and income statements, determining short-term debt 
issuance and short-term investments, calculating operating expenses 
and taxes, and computing capital distributions. Input data include 
an Enterprise's balance sheet at the beginning of the stress period, 
interest rates, and the outputs from cash flow components of the 
stress test. The outputs of the procedures discussed in this 
section--120 monthly pro forma balance sheets and income 
statements--are the basis for the capital calculation described in 
section 3.12, Calculation of the Risk-Based Capital Requirement, of 
this Appendix.

3.10.2  Inputs

    This component uses the data described in section 3.10.2.1, 
Enterprise Data, section 3.10.2.2, Interest Rates, and section 
3.10.2.3, Outputs From Cash Flow Components of the Stress Test, to 
produce monthly pro forma balance sheets and income statements for 
the Enterprises.

3.10.2.1  Enterprise Data

    [a] In addition to the starting position data described in the 
cash flow components, the Enterprises provide the dollar values for 
the following starting position balances:
     Amounts required to reconcile starting position 
balances from cash flow components of the stress test with an 
Enterprise's balance sheet (e.g., differences between actual and 
estimated loan prepayments during the last few days in the month)
     Cash
     Low income housing tax credit investments
     Unamortized balances of premiums, discounts, and fees 
from the acquisition of retained whole loans and retained mortgage-
related securities at other than par value
     Allowances for loan losses
     Accrued interest receivable on retained whole loans, 
retained mortgage-backed securities, mortgage-linked derivatives, 
and nonmortgage investments
     Amounts receivable from index sinking fund debentures, 
currency swaps, fees, income taxes, and other accounts receivable
     Real estate owned
     Fixed assets
     Clearing accounts
     Unamortized premiums, discounts and fees related to 
debt securities
     Unamortized balances related to the sold portfolio
     Deferred balances related to liability-linked 
derivatives
     Accrued interest payable
     Principal and interest payable to mortgage security 
investors
     Other liabilities (e.g., payables from currency swaps, 
escrow deposits, and income taxes)
     Dividends payable
     Components of stockholder's equity (i.e., common stock, 
preferred stock, paid-in capital, retained earnings, treasury stock, 
and unrealized gains and losses on available-for-sale securities)
    (b) Other data provided by the Enterprises include:
     Operating expenses for the quarter prior to the 
beginning of the stress test
     Earnings before income taxes and provision for income 
taxes for the three years prior to the beginning of the stress test
     Year-to-date income before taxes and provision for 
income taxes
     Dividend payout ratio for the four quarters prior to 
the beginning of the stress test
     Minimum capital requirement at the beginning of the 
stress test

3.10.2.2  Interest Rates

    This component of the stress test requires the following 
interest rates generated by the Interest Rates component described 
in section 3.3, Interest Rates, of this Appendix:
     Six-month Federal agency cost of funds
     Six-month constant maturity Treasury yield

3.10.2.3  Outputs From Cash Flow Components of the Stress Test

    This component of the stress test also requires monthly cash 
flows generated as described in section 3.9, Cash Flows, for:
     Whole Loans (section 3.9.1)
     Mortgage-Related Securities (section 3.9.2)
     Non-Mortgage Investment and Investment-Linked 
Derivative Contract Cash Flows (section 3.9.4)
     Debt and Related Cash Flows (section 3.9.3)

3.10.3  Procedures

    The stress test calculates new debt and investments, dividends, 
allowances for loan losses, operating expenses, and income taxes. 
These calculations are both determined by and affect the pro forma 
balance sheets and income statements over the stress period.

[[Page 18297]]

3.10.3.1  New Debt and Investments

    (a) The availability of cash in each month of the stress period 
determines whether cash is invested, or whether borrowings are 
required. The stress test calculates cash received and cash 
disbursed each month in order to determine the net availability of 
cash. The following describe the many ``sources'' and ``uses'' of 
cash.
    1. Cash sources include:
     Cash at the beginning of the stress test
     Principal and interest payments from retained mortgages 
and retained mortgage-backed securities
     Principal and interest payments from non-mortgage 
investments (e.g., Federal funds sold, mortgage securities purchased 
under agreements to resell, commercial paper, eurodollar time 
deposits, asset-backed securities, U.S. Treasury securities, 
municipal obligations, auction-rate preferred stock)
     Amounts received from counterparties on derivative 
contracts
      Disposition of foreclosed property included in the 
balance sheet at the beginning of the stress test
     Amounts received from other assets and receivables 
included in the balance sheet at the beginning of the stress test 
(e.g., receivables from index sinking fund debentures and currency 
swaps, Federal income taxes refundable.)
     Guarantee fees
     Float income on principal and interest received on the 
sold portfolio
      Federal income tax refunds from net operating loss 
(NOL) carrybacks
     Recoveries on defaulted loans
    2. Cash uses include:
     Repayment of principal to investors on debt instruments 
(as they mature or are called)
     Interest paid to investors on debt instruments
     Amounts paid to counterparties on derivative contracts
     Principal payments to investors (net of recoveries) due 
to mortgage defaults on loans in the sold portfolio
     Payments of miscellaneous liabilities included in the 
balance sheet at the beginning of the stress test, e.g., some 
accounts payable, escrow deposits, principal and interest due to 
mortgage security investors, and payables from currency swaps 
(Amounts recorded subsequent to the beginning of the stress period 
as principal and interest due mortgage securities investors do not 
affect the cash calculation for new debt and investments.)
     Operating expenses
     Income taxes
     Dividends on preferred and common stock
    (b) During the stress period, the net cash position for each of 
the 120 months is calculated at the end of each month. Timing of 
sources and uses of cash within each month are ignored.
    (c) At the end of any month in which the cash position is 
calculated to be negative, the stress test issues six month discount 
notes at the six month Federal Agency Cost of Funds rate, plus a 2.5 
basis point issuance cost. When the cash position is positive, the 
stress test invests the Enterprise's excess cash in one month 
maturity assets at a rate equivalent to the six month Treasury 
yield. As a result, the cash position of an Enterprise is zero at 
the end of each month during the stress test.

3.10.3.2  Dividends

    (a) The stress test determines quarterly whether to pay 
preferred and common dividends and, if so, how much based on the 
rules that follow.
    1. Preferred Stock--An Enterprise will pay dividends on 
preferred stock as long as that Enterprise meets the estimated 
minimum capital requirement before and after the payment of these 
dividends. Preferred stock dividends are based on the coupon rates 
of the issues outstanding. The coupon rates for any issues of 
variable rate preferred stock are calculated using projections of 
the appropriate index rate.
    2. Common Stock--In the first year of the stress test, dividends 
on common stock in all four quarters are based on the trend in 
earnings at that Enterprise. If earnings are positive and 
increasing, dividends are paid based on the same percent dividend 
payout as the average payout of the preceding four quarters. If 
earnings are not positive and increasing, dividends are paid based 
on the preceding quarter's dollar amount of dividends per share. 
Common stock dividends are stopped after four quarters of payouts, 
except they are cut off earlier if an Enterprise's capital falls 
below the minimum capital requirement.
    3. No other net capital distributions are made, i.e., no 
repurchases of common stock or redemption of preferred stock occur 
during the stress test.
    (b) The Enterprise's minimum capital requirement is computed by 
applying leverage ratios to all assets (2.50 percent) and off-
balance sheet obligations (0.45 percent), and summing the results.

3.10.3.3  Allowances for Loan Losses and Other Charge-Offs

    (a) The stress test calculates a tentative allowance for loan 
losses monthly by multiplying current month mortgage default losses 
\19\ by twelve, thus annualizing current month mortgage default 
losses. If the tentative allowance for loan losses for the current 
period is greater than the balance from the prior month plus charge-
offs for the current month, a provision (e.g., expense) is recorded. 
Otherwise, no provision is made and the allowance for loan losses is 
equal to the prior period amount less current month charge-offs.
---------------------------------------------------------------------------

    \19\ Current month mortgage default losses include the sum of 
what the Enterprises classify as ``provision for losses'' and 
``foreclosed property expense.'' For both the retained and sold 
portfolios, this includes lost principal (net of recoveries from 
credit enhancements and disposition of the real estate collateral), 
and foreclosure, holding, and disposition costs.
---------------------------------------------------------------------------

    (b) Other charge-offs result from ``haircuts'' related to 
mortgage revenue bonds, private-issue MBS, and non-mortgage 
investments, described in their respective cash flow components. 
These haircuts result in receipt of less than the amount of 
principal contractually due. This lost principal is charged-off when 
due and not received.

3.10.3.4  Operating Expenses

    The stress test calculates operating expenses, which include 
non-interest costs such as those related to an Enterprise's salaries 
and benefits, professional services, property, equipment and office. 
Over the stress period, operating expenses decline in proportion to 
the decline in the size of an Enterprise's mortgage portfolio (i.e., 
the sum of outstanding principal balances of its retained and sold 
mortgage portfolios). The stress test calculates the percentage of 
an Enterprise's mortgage portfolio at the start of the stress test 
that is remaining at the end of each month of the stress period. It 
then multiplies the percentage of assets remaining by one-third of 
the Enterprise's operating expenses in the quarter immediately 
preceding the start of the stress test. The resulting amount is an 
Enterprise's operating expense for a given month in the stress 
period.

3.10.3.5  Taxes

    [a] Both Enterprises are subject to Federal income taxes, but 
neither is subject to state or local income taxes.
    [b] The stress test applies an effective Federal income tax rate 
of 30 percent when calculating the monthly provision for income 
taxes (e.g., income tax expense). This tax rate is lower than the 
statutory rate because of tax exempt interest received, deductions 
for dividends received, and equity investments in affordable housing 
projects. OFHEO may change the 30 percent income tax rate if there 
are significant changes in Enterprise experience or changes in the 
statutory income tax rate.
    [c] The stress test sets income tax expense for tax purposes 
equal to the provision for income taxes. The effects of timing 
differences between taxable income and generally accepted accounting 
principles (GAAP) income before income taxes are ignored. Therefore, 
Net Operating Loss (NOL) occurs only when the net income, before the 
provision for income taxes, is negative.
    [d] Payments for estimated income taxes are made quarterly. At 
the end of each year, the annual estimated tax amount is compared to 
the annual actual tax amount. At that time, a payment of remaining 
taxes is made or a refund for overpayment of income taxes is 
received.
    [e] A NOL for the current month is ``carried back'' to offset 
taxes in any or all of the preceding three calendar years. (The 
Enterprises' tax year is the same as the calendar year.) This offset 
of the prior years' taxes results in a negative provision for income 
taxes (e.g., income) for the current month. Use of a carry back 
reduces available carry backs in subsequent months. Any NOL 
remaining after carry backs are exhausted becomes a carry forward.
    [f] Carry forwards represent NOLs that cannot be carried back to 
offset previous years' taxes, but can be used to offset taxes in any 
or all of the subsequent 15 years. Carry forwards accumulate until 
used, or until they expire 15 years after they are generated.
    [g] Under the stress test, the Enterprises will not have a 
positive net income in future

[[Page 18298]]

years to utilize NOL carry forwards. A valuation adjustment is used 
to decrease the Federal income tax refundable to zero (e.g., the 
amount likely to be realized).

3.10.3.6  Accounting

    [a] The 1992 Act specifies that total capital includes core 
capital and a general allowance for foreclosure losses. For the 
Enterprises, this general allowance is represented by general 
allowances for loan losses on their retained and sold mortgage 
portfolios. The 1992 Act further defines core capital as the sum of 
the following components of equity:
     The par or stated value of outstanding common stock
     The par or stated value of outstanding perpetual, 
noncumulative preferred stock
     Paid-in capital
     Retained earnings
    [b] In order to determine the amount of total capital an 
Enterprise must hold to maintain positive total capital throughout 
the ten-year stress period, the stress test projects the above four 
components of equity plus general loss allowances as part of the 
monthly pro forma balance sheets and income statements.
    [c] Details of an Enterprise's actual balance sheet at the 
beginning of the stress test are recorded from a combination of 
starting position balances for all instruments for which other 
components of the stress test calculates cash flows and other 
starting position balances for assets, liabilities, and equity 
accounts needed to complete an Enterprise's balance sheet.
    [d] After recording an Enterprise's balance sheet at the 
beginning of the stress period, the stress test creates monthly pro 
forma balance sheets and income statements by recording output from 
the cash flow components of the stress test; recording new debt and 
investments (and related interest), dividends, loss allowances, 
operating expenses, and taxes; and applying accounting rules 
pertaining to balance sheets and pro forma income statements.

3.10.3.6.1  Accounting for Positions and Cash Flows From Cash Flow 
Components

    Balances at the beginning of the stress test and subsequent 
changes to related pro forma balance sheet and income statement 
accounts are obtained from data generated by cash flow components of 
the stress test for the following:
    1. Retained whole loan mortgage interest cash flows in the first 
month of the stress period reduce accrued interest receivable at the 
beginning of the stress test. Subsequent months interest cash flows 
are recorded as accrued interest receivable and interest income in 
the month prior to its receipt. When the interest cash flows are 
received, accrued interest receivable is reduced. Monthly principal 
cash flows (including prepayments and defaulted principal) are 
recorded as reductions in the outstanding balance of the loan group. 
Net losses on defaults are charged off against the allowance for 
loan losses. Recoveries are cash inflows.
    2. Retained mortgage-backed security interest cash flows in the 
first month of the stress period reduce accrued interest receivable 
at the beginning of the stress test. Subsequent months interest cash 
flows are recorded as accrued interest receivable and interest 
income in the month prior to its receipt. When the interest cash 
flows are received, accrued interest receivable is reduced. Monthly 
principal cash flows (including prepayments) are recorded in the 
month received as a reduction in the outstanding balance of mortgage 
assets.
    3. Mortgage revenue bond monthly interest cash flows in the 
first month of the stress period reduce accrued interest receivable 
at the beginning of the stress test. Subsequent months interest cash 
flows are recorded as accrued interest receivable and interest 
income in the month prior to its receipt. When the interest cash 
flows are received, accrued interest receivable is reduced. Monthly 
principal cash flows are recorded as reductions in the outstanding 
balance of mortgage assets. Defaulted principal is charged-off when 
due and not received.
    4. Principal repayments from non-mortgage investments (e.g., 
Federal funds sold; mortgage securities purchased under agreements 
to resell; commercial paper; eurodollar time deposits; asset-backed 
securities; U.S. Treasury securities; municipal obligations, other 
than mortgage revenue bonds; and auction-rate preferred stock) 
reduce the investment and increase cash. Interest payments received 
increase cash and reduce accrued interest receivable. Accrued 
interest receivable includes both amounts at the beginning of the 
stress period and subsequent monthly accruals (also recorded as 
interest income).
    5. Sold portfolio cash flows include monthly guarantee fees, 
float, and principal and interest due MBS investors. Guarantee fees 
are recorded as income in the month received. Principal and interest 
due mortgage security investors does not affect the balance sheet; 
however, interest earned on these amounts (float) is recorded as 
income in the month the underlying principal and interest payments 
are received. Principal payments received and defaulted loan 
balances reduce the outstanding balance of the sold portfolio. 
Losses (net of recoveries) are charged off against the allowance for 
losses on the sold portfolio (a liability on the pro forma balance 
sheets) and reduce cash.
    6. For each debt instrument in the starting position, interest 
is accrued monthly. Accrued interest (representing both amounts as 
of the beginning of the stress period and subsequent monthly 
accruals) and principal debt due investors are reduced when cash 
payments are made.
    7. Issuance of discount notes increases cash by the amount of 
the new debt, net of discounts and issuance costs. Interest expense 
is accrued monthly and paid at maturity when the discount note is 
retired at par. Discounts and issuance costs are amortized on a 
straight line basis over the life of the discount note, increasing 
interest expense.
    8. The amortized balance (e.g., the face amount of the debt less 
the unamortized discount) of zero coupon debt is recorded in the 
starting position. The unamortized discount is amortized monthly 
using the level yield method over the debt's term to maturity and 
recorded as interest expense. At maturity, the face amount of the 
debt is paid to investors and the balance of debt is reduced.

3.10.3.6.2  Accounting for Other Changes in Starting Position Balances

    Cash flows, income, and changes in the pro forma balances for 
other parts of the Enterprise's balance sheet are recorded as 
described below.
    1. Unrealized gains (losses) on available-for-sale investments 
included in the balance sheet at the beginning of the stress test 
are recorded as income during the first month of the stress test. 
Recognition of unrealized gains increases earnings; recognition of 
unrealized losses decreases earnings.
    2. Unamortized balances of premiums, discounts, and fees from 
the acquisition of retained loans and retained mortgage-backed 
securities at other than par value are a component of the balance 
sheet at the beginning of the stress test. Unamortized balances 
related to retained whole loans are amortized in proportion to the 
decline in the size of an Enterprise's retained portfolio. 
Unamortized balances related to REMICs and strips are amortized over 
their lives using the level yield method, calculated using cash 
flows generated from the cash flow component of the stress test. 
Amortizing deferred balances at the beginning of the stress test 
reduces the deferred amounts on the balance sheet by simultaneously 
increasing interest income by amortizing discounts and decreasing 
interest income by amortizing premiums.
    3. Low income housing tax credit investments at the beginning of 
the stress test remain constant over the stress test. No earnings or 
expenses are directly recorded.
    4. The following receivables at the beginning of the stress test 
are converted to cash in the first month of the stress test:
     Amounts receivable from index sinking fund debentures 
and currency swaps
     Other miscellaneous receivables (e.g., fees receivable 
and accounts receivable)
     Federal income taxes
    5. Real estate owned at the beginning of the stress test is 
converted to cash on a straight-line basis over the first six months 
of the stress test.
    6. Clearing accounts as of the beginning of the stress test are 
converted to cash on a straight-line basis over the first twelve 
months of the stress test.
    7. Fixed assets at the beginning of the stress test remain 
constant over the stress test. Depreciation is included in the base 
on which operating expenses are calculated for each month during the 
stress period.
    8. Unamortized premiums, discounts and fees related to debt 
securities at the beginning of the stress test are amortized on a 
level yield basis over the remaining term to contractual maturity of 
the debt. Specifically, unamortized amounts are grouped by term to 
maturity and coupon bucket for debentures, zero coupon instruments, 
and all other debt. Unamortized amounts are amortized on a level 
yield basis using weighted average maturities and weighted average 
coupons for each of these groups.
    9. Deferred balances relating to liability-linked derivatives at 
the beginning of the stress test are amortized using the sum of 
years digits method over three years.

[[Page 18299]]

Amortizing deferred balances increases or decreases interest 
expense, as appropriate.
    10. Principal and interest payable to an Enterprise's mortgage 
security investors at the beginning of the stress test are paid 
during the first two months of the stress test (one-half in month 
one and one-half in month two).
    11. The following liabilities at the beginning of the stress 
test are paid in the first month of the stress test, reducing cash:
     Payables from currency swaps
     Escrow deposits
    12. Unamortized balances related to the sold portfolio are 
amortized in proportion to the decline in the size of an 
Enterprise's sold portfolio.

3.10.3.6.3 Other Accounting Principles

    Additional accounting principles that affect the pro forma 
balance sheets and income statements over the stress period are also 
applied.
    1. All investment securities are treated as held to maturity. As 
such, they are recorded as assets at amortized cost, not at fair 
value.
    2. Enterprise REIT subsidiaries are consolidated. Specifically, 
REIT assets are treated as Enterprise assets. Preferred stock of the 
REIT is reflected as Enterprise debt. Dividends paid on the 
preferred stock are reported as interest expense.
    3. Dividends are declared and paid simultaneously.
    4. Treasury stock is reflected as a reduction in retained 
earnings.

3.10.4 Output

    For each month of the stress period, the stress test produces a 
pro forma balance sheet and income statement. These pro forma 
financial statements are the inputs for calculating capital.

3.11 Treatment of New Enterprise Activities

    [a] Given rapid innovation in the financial services industry, 
OFHEO anticipates the Enterprises will become involved with new 
mortgage products, investments, debt and derivative instruments, and 
business activities that the stress test will have to accommodate. 
OFHEO will monitor the Enterprises' activities and, when 
appropriate, propose amendments to this regulation addressing the 
treatment of new instruments and activities. However, the regulation 
is sufficiently flexible and complete to address new Enterprise 
activities as they emerge.
    [b] Credit and interest rate risk of new Enterprise activities 
and instruments will be reflected in the stress test by simulating 
their credit and cash flow characteristics using approaches 
described throughout this Appendix. Simulating new activities and 
instruments will require that the Enterprises provide complete data, 
and full explanations of their operation. To the extent that 
approaches described herein are not applicable directly, OFHEO will 
combine and adapt them in an appropriate manner. For example, the 
stress test might employ its mortgage performance components and 
adapt its cash flow components to accurately simulate the loss 
mitigating effects of credit derivatives. Where there is no 
reasonable approach using existing combinations or adaptations 
within the timeframe for computing a quarterly capital calculation, 
the stress test will employ an appropriately conservative treatment, 
consistent with OFHEO's role as a safety and soundness regulator. 
Such treatment will continue until such time as sufficient 
information is made available to justify an alternative treatment, 
which may be subsequently incorporated as a specific provision in 
this Appendix.
    [c] Procedurally, the Enterprises are expected to notify OFHEO 
of proposals related to new products, investments or instruments 
before they are purchased or sold or as soon thereafter as possible, 
but in any event no later than in connection with submission of the 
risk-based capital report provided for in Sec. 1750.12. OFHEO will 
provide the Enterprise with its estimate of the capital treatment as 
soon thereafter as possible. The Enterprise will also be notified of 
the capital treatment in accordance with the notice of proposed 
capital classification provided for in Sec. 1750.21.

3.12 Calculation of the Risk-Based Capital Requirement

3.12.1 Overview

    [a] The stress test determines the minimum amount of total 
capital that an Enterprise must hold at the start of the stress test 
in order to maintain positive total capital throughout the ten-year 
stress period. Once the stress test has determined this amount of 
starting capital, the final calculation in the regulation is the 
Calculation of the Risk-Based Capital Requirement.
    [b] The first step in calculating the minimum amount of total 
capital is to compute the discounted present value (as of the start 
of the stress test) of the projected month-end total capital amounts 
for each month of the stress period for both interest rate 
scenarios. The second step is to identify the lowest of the 
resulting 240 monthly discounted values and subtract from it the 
capital amount required for ``other'' off-balance sheet guarantees. 
If the resulting net amount is positive, the Enterprise has more 
than enough capital to maintain positive capital during the stress 
period. If the resulting net amount is negative, the Enterprise's 
capital at the start of the stress test is not sufficient. The third 
step is to subtract this net amount from the capital the Enterprise 
holds at the start of the stress test. This step effectively 
subtracts the extra capital or adds the shortfall to obtain the 
minimum amount of capital that the Enterprise needs at the start of 
the stress test.
    [c] The final step in the regulation is the calculation of the 
Enterprise's risk-based capital requirement. The risk-based capital 
requirement equals the adjusted capital amount times 1.3 to account 
for management and operations risk.

3.12.2 Inputs

    [a] The above calculations use outputs from three components of 
the stress test to make the final two capital calculations. These 
components include section 3.3, Interest Rates; section 3.8, Other 
Off-Balance Sheet Guarantees; and section 3.10, Operations, Taxes, 
and Accounting, of this Appendix.
    [b] For each month of the stress test, the following inputs are 
from pro forma financial statements projected by the Operations, 
Taxes, and Accounting component:
     Total capital (the par or stated value of outstanding 
common stock, the par or stated value of outstanding perpetual, 
noncumulative preferred stock, paid-in capital, retained earnings, 
and allowance for losses on retained and sold mortgages)
     Provision for income taxes (income tax expense)
     Valuation adjustment that reduces benefits recorded 
from net operating losses when no net operating loss tax carrybacks 
are available
     Discount notes (amount outstanding)
    [c] For present-value calculations, the stress test uses either 
the six month Federal agency cost of funds or the six month Treasury 
yield generated by section 3.3, Interest Rates of this Appendix.
    [d] The input for the capital amount for other off-balance sheet 
guarantees is obtained from section 3.8, Other Off-Balance Sheet 
Guarantees, of this Appendix.

3.12.3 Procedures

    The following steps are used for determining the minimum total 
capital an Enterprise needs to maintain positive capital during the 
stress test and the risk-based capital requirement for the 
Enterprise.
    1. Determine whether taxes are owed or tax refunds will be 
received. If the provision for income taxes is positive (reflecting 
taxes owed) or negative (reflecting tax refunds to be received), 
then the effective tax rate is 30 percent. If the provision for 
income taxes is zero (after valuation adjustments, implying that 
income is negative, but no net operating loss tax carrybacks are 
available), then the effective tax rate is zero.
    2. Determine whether an Enterprise is an investor or a borrower 
in each month of the stress period. In months where an Enterprise 
has outstanding six-month discount notes that were issued during the 
stress test, then the Enterprise is a borrower. Otherwise, the 
Enterprise is an investor.
    3. Determine the appropriate monthly discount factor for each 
month of the stress period. In months where an Enterprise is an 
investor, the monthly discount factor is based on the yield of 
short-term assets:
[GRAPHIC] [TIFF OMITTED] TP13AP99.184


[[Page 18300]]


    In months where an Enterprise is a borrower, the monthly 
discount factor is based on the cost of the Enterprises' short-term 
debt:
[GRAPHIC] [TIFF OMITTED] TP13AP99.185

[GRAPHIC] [TIFF OMITTED] TP13AP99.368

    4. Compute the cumulative discount factor for the total capital 
amount for each month in the stress period--The cumulative discount 
factor for a given month of the stress period is the monthly 
discount factor for that month multiplied by the cumulative discount 
factor for the preceding month. (The cumulative discount factor for 
the first month of the stress period is the monthly discount factor 
for that month.) Thus, the cumulative discount factor for any month 
incorporates all of the previous monthly discount factors.
    5. Compute discounted total capital for each month of the stress 
period for both interest rate scenarios. Divide the total capital 
for a given month by the cumulative discount factor for that month.
    6. Compute the amount of capital necessary to maintain positive 
capital throughout the stress period. Identify the lowest discounted 
total capital amount from among the 240 monthly discounted total 
capital amounts. Subtract the capital required for ``other'' off-
balance sheet guarantees as calculated in section 3.8, Other Off-
Balance Sheet Guarantees, component of the stress test from the 
lowest discounted amount. Then subtract the resulting difference 
from the Enterprise's total capital at the start of the stress 
period. This subtraction effectively reduces the starting capital 
amount by any extra capital that remains at the end of the stress 
period or increases starting capital by any shortfall. The resulting 
number is the starting capital amount that the Enterprise must hold 
in order to maintain positive total capital throughout the stress 
period.
    7. Compute the risk-based capital requirement. Multiply the 
capital amount calculated in Step 6, by 1.3 for management and 
operations risk.

3.12.4  Output

    The output of the above calculations is the risk-based capital 
requirement for an Enterprise at the start date of the stress test.
    5. Add new subpart C to read as follows:

Subpart C--Capital Classification

Sec.
1750.20  Definitions.
1750.21  Notice of capital classification.

Subpart C--Capital Classification


Sec. 1750.20  Definitions

    All of the terms defined at Sec. 1750.2 shall have the same meaning 
for purposes of this subpart C.


Sec. 1750.21  Notice of capital classification

    (a) Pursuant to section 1364 of the 1992 Act (12 U.S.C. 4614), 
OFHEO is required to determine the capital classification of each 
Enterprise on a not less than quarterly basis.
    (b) The determination of the capital classification shall be made 
following a notice to, and opportunity to respond by, the Enterprise.
    (1) Not later than 60 calendar days after the date for which the 
minimum capital report required by Sec. 1750.3 and the risk-based 
capital report required by Sec. 1750.12 are filed, OFHEO will provide 
each Enterprise with a notice of proposed capital classification. The 
notice shall contain the following information:
    (i) The proposed capital classification;
    (ii) The proposed minimum capital requirement;
    (iii) The summary computation of the proposed minimum capital 
requirement;
    (iv) The proposed risk-based capital level; and
    (v) The summary computation of the proposed risk-based capital 
level.
    (2) Each Enterprise shall have a period of 30 calendar days 
following receipt of a notice of proposed capital classification to 
submit a response regarding the proposed capital classification. The 
response period may be extended for up to 30 additional calendar days 
at the sole discretion of the Director. The Director may shorten the 
response period with the consent of the Enterprise, or without such 
consent if the Director determines that the condition of the Enterprise 
requires a shorter period.
    (3) The Director shall take into consideration any response to the 
notice of proposed capital classification received from the Enterprise 
and shall issue a notice of final capital classification for each 
Enterprise not later than 30 calendar days following the end of the 
response period.
    (c) From [insert date of publication of the final rule in the 
Federal Register] until [insert date twelve months after date of 
publication of the final rule in the Federal Register], the Director 
shall determine the capital classification of the Enterprise, based 
solely on the proposed minimum capital requirement.

    Dated: April 5, 1999.
Mark A. Kinsey,
Acting Director, Office of Federal Housing Enterprise Oversight.
[FR Doc. 99-8808 Filed 4-12-99; 8:45 am]
BILLING CODE 4220-01-P